Forest use suitability:Towards decision-making-oriented sustainable management of forest ecosystem services

Management of forest lands considering multi-functional approaches is the basis to sustain or enhance the provi-sion of specific benefits,while minimizing negative impacts to the environment.Defining a desired management itinerary to a forest depends on a variety of factors,including the forest type,its ecological characteristics,and the social and economic needs of local communities.A strategic assessment of the forest use suitability(FUS)(namely productive,protective,conservation-oriented,social and multi-functional)at regional level,based on the provision of forest ecosystem services and trade-offs between FUS alternatives,can be used to develop management strategies that are tailored to the specific needs and conditions of the forest.The present study assesses the provision of multiple forest ecosystem services and employs a decision model to identify the FUS that sup-ports the most present and productive ecosystem services in each stand in Catalonia.For this purpose,we apply the latest version of the Ecosystem Management Decision Support(EMDS)system,a spatially oriented decision support system that provides accurate results for multi-criteria management.We evaluate 32 metrics and 12 as-sociated ecosystem services indicators to represent the spatial reality of the region.According to the results,the dominant primary use suitability is social,followed by protective and productive.Nevertheless,final assignment of uses is not straightforward and requires an exhaustive analysis of trade-offs between all alternative options,in many cases identifying flexible outcomes,and increasing the representativeness of multi-functional use.The assignment of forest use suitability aims to significantly improve the definition of the most adequate management strategy to be applied.

Compensation for forest ecological services in China

The paper discusses methods to compensate for the costs incurred in the supply of forest ecological services （FES）, i.e. government dominated and market-based instruments as well as progress made so far in China. Factors which constrain the supply of these services and potential policy improvements are presented.

Growth trends and environmental drivers of major tree species of the northern hardwood forest of eastern North America

The future health and productivity of tree species in the northern hardwood forest of eastern North America are uncertain considering changes in climate and pollution loading there.To better understand the trajectory of the northern hardwood forest,we studied the growth of three tree species emblematic of it:sugar maple(Acer saccharum Marsh),American beech(Fagus grandifolia Ehrh.),and yellow birch(Betula alleghaniensis Britton),plus a fourth species,red maple(Acer rubrum L.),whose abundance has increased in the region.We also analyzed the link between growth and several factors for690 trees in 45 plots throughout Vermont,USA:tree age and size,site elevation,and climate and acid deposition variables.Throughout their chronologies(1945-2014),all four species exhibited increasing growth followed by plateaued growth indicative of a maturing forest.For all species,summer moisture was positively correlated with growth,summer temperature was negatively associated with growth,and winter moisture or snow were positively correlated with growth.This last association was expected for sugar maple.However,our data suggest that winter snowpack may be more broadly relevant in sustaining tree growth in a region where snow has historically insulated the soil from freezing that can damage roots and lead to reduced aboveground growth.Measures of pollution deposition were also correlated with growth for all species except American beech—a species with documented tolerance to pollutant inputs.Of the four species studied,red maple had the fewest associations with environmental variables,which suggests that it may be less susceptible to growth reductions as the climate changes.

Addressing nonresponse bias in forest inventory change estimation using response homogeneity classifications

Estimating amounts of change in forest resources over time is a key function of most national forest inventories(NFI). As this information is used broadly for many management and policy purposes, it is imperative that accurate estimations are made from the survey sample. Robust sampling designs are often used to help ensure representation of the population, but often the full sample is unrealized due to hazardous conditions or possibly lack of land access permission. Potentially, bias may be imparted to the sample if the nonresponse is nonrandom with respect to forest characteristics, which becomes more difficult to assess for change estimation methods that require measurements of the same sample plots at two points in time, i.e., remeasurement. To examine potential nonresponse bias in change estimates, two synthetic populations were constructed: 1) a typical NFI population consisting of both forest and nonforest plots, and 2) a population that mimics a large catastrophic disturbance event within a forested population. Comparisons of estimates under various nonresponse scenarios were made using a standard implementation of post-stratified estimation as well as an alternative approach that groups plots having similar response probabilities(response homogeneity). When using the post-stratified estimators, the amount of change was overestimated for the NFI population and was underestimated for the disturbance population, whereas the response homogeneity approach produced nearly unbiased estimates under the assumption of equal response probability within groups. These outcomes suggest that formal strategies may be needed to obtain accurate change estimates in the presence of nonrandom nonresponse.

Do forest health threats affect upland oak regeneration and recruitment?Advance reproduction is a key co-morbidity

We analyzed national forest inventory data collected from circa 2000–2018 across 37 states in the eastern United States to better understand the influence of forest health related canopy disturbances on the regeneration and recruitment dynamics of upland oaks(Quercus).We found low levels of oak recruitment across all disturbance types examined but limited evidence of any direct effects from the type of disturbance on the population of regenerating oaks.The general lack of differences in oak regeneration response between forest health disturbances and disturbances caused by harvested or non-disturbed plots does not indicate that the effects of forest health disturbances were benign,however.Instead,low level of oak recruitment across all disturbance types highlights the pervasiveness of the trend of shifting composition in once oak-dominated forests where oak is absent or sparse in the regeneration layer.Our results show that oak recruitment was higher when oak was present as advance reproduction prior to disturbance from any cause examined.Collectively,these results lead us to conclude that the widespread inadequacy of oak advance reproduction in mature oak-dominated forests is the prevailing threat to oak forest health and sustainability.We suggest the status of advance reproduction be treated as a co-morbidity when weighing the risk and potential outcomes from other threats to upland oak forests in the eastern United States.

Taxonomic and community composition of epigeal arthropods in monoculture and mixed tree species plantations in a deciduous forest of Ghana

Tropical forests provide several ecosystem services and functions and support approximately two-thirds of the world’s biodiversity but are seriously threatened by deforestation.Approaches to counteract this menace have revolved around aff orestation with several or a single tree species.We thus investigated how plantation forests with either a single or several tree species infl uenced arthropod taxonomic and community composition using pitfall traps to sample selected groups of epigeal arthropods(Araneae,Coleoptera,Orthoptera and Hymenoptera)and with environmental variables assessed simultaneously.Our results revealed 54 taxonomic groups with signifi cantly higher taxonomic richness,activity density,and diversity in the mixed stands than in the monoculture stands.The significant differences in community composition were mainly driven by families including Lycosidae,Formicidae,Staphylinidae,Scotylidae,Hydrophilidae,Gryllidae and Scarabaeidae and were explained by distinct habitat characteristics(canopy openness,litter depth,deadwood volume,and tree height).While the diverse tree communities and heterogeneous vegetation structure off ered food and habitat resources for diverse arthropod groups,the allelopathic nature coupled with homogenous stand characteristics of the Tectona grandis stands in the monoculture suppressed the growth of understorey vegetation that could otherwise serve as food and habitat resources for arthropods,which might have led to limited activities and diversity of arthropods in the monoculture plantation stands.The fi ndings thus highlight the need to promote mixed tree plantations in degraded tropical areas,especially when restoring biodiversity is the prime management focus.

Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decisionmaking.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

Future impacts of climate change on forest fire danger in northeastern China

Climate warming has a rapid and far-reaching impact on forest fire management in the boreal forests of China. Regional climate model outputs and the Canadian Forest Fire Weather Index （FWI） Sys- tem were used to analyze changes to fire danger and the fire season for future periods under IPCC Special Report on Emission Scenarios （SRES） A2 and B2, and the data will guide future fire management planning. We used regional climate in China （1961 1990） as our validation data, and the period （1991–2100） was modeled under SRES A2 and B2 through the weather simulated by the regional climate model system （PRECIS）. Meteorological data and fire danger were interpolated to 1 km 2 by using ANUSPLIN software. The average FWI value for future spring fire sea- sons under Scenarios A2 and B2 shows an increase over most of the region. Compared with the baseline, FWI averages of spring fire season will increase by 0.40, 0.26 and 1.32 under Scenario A2, and increase by 0.60, 1.54 and 2.56 under Scenario B2 in 2020s, 2050s and 2080s, respectively. FWI averages of autumn fire season also show an increase over most of the region. FWI values increase more for Scenario B2 than for Scenario A2 in the same periods, particularly during the 2050s and 2080s. Average future FWI values will increase under both scenarios for autumn fire season. The potential burned areas are expected to increase by 10% and 18% in spring for 2080s under Scenario A2 and B2, respectively. Fire season will be prolonged by 21 and 26 days under ScenariosA2 and B2 in 2080s respectively.

Use of models in large-area forest surveys： comparing model-assisted, model-based and hybrid estimation

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 design- based 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, model- based, 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.

The national forest inventory in China:history-results-international context

Background： National forest resource assessments Inventories （NFI＇s）, constitute an important nationa and monitoring, commonly known as National Forest 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 20th and 21st centuries, with some reference to Europe and the US; · highlights the emergence of some common international themes： consistency of measurement; sampling designs; implementation of improved technology; expansion of the variables monitored more efficient 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.

Afforestation,restoration and regeneration——Not all trees are created equal

Undulations in weather patterns have caused climate shifts of increased frequency and duration around the world. The need for additional research and model data on this pressing problem has resulted in a plethora of research groups examining a particular tree species or biome for negative effects of climate change. This review aims to （1） collect and merge recent research data on regeneration within old- and new-growth forests, （2） highlight and expand upon selected topics for additional discussion, and （3） report how shade tolerance, drought toler- ance, and inherent plasticity affect tree growth and development. Al- though shade and drought tolerance have been well studied by a number of research groups, this review reveals that in-depth analysis of a single or a few species in a given area will not generate the data required to implement a successful regeneration plan. Studies using historical accounts of previous species composition, information regarding site sea- sonality, species competition, and individual responses to drought and shade are needed to （1） develop best management plans and （2） ensure future modeling experiments are focused on a greater variety of species using more innovative methods to evaluate climate change effects.

Changes in soil organic carbon contents and fractionations of forests along a climatic gradient in China

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.

Young and old forest in the boreal:critical stages of ecosystem dynamics and management under global change

The circumboreal forest encompasses diverse landscape structures, dynamics and forest age distributions determined by their physical setting, and historical and current disturbance regimes. However, due to intensifying forest utilisation, and in certain areas due to increasing natural disturbances, boreal forest age-class structures have changed rapidly, so that the proportion of old forest has substantially declined, while that of young post-harvest and post-natural-disturbance forest proportions have increased. In the future, with a warming climate in certain boreal regions, this trend may further be enhanced due to an increase in natural disturbances and large-scale use of forest biomass to replace fossil-based fuels and products.The major drivers of change of forest age class distributions and structures include the use of clearcut shortrotation harvesting, more frequent and severe natural disturbances due to climate warming in certain regions. The decline in old forest area, and increase in managed young forest lacking natural post-disturbance structural legacies,represent a major transformation in the ecological conditions of the boreal forest beyond historical limits of variability.This may introduce a threat to biodiversity, ecosystem resilience and long-term adaptive capacity of the forest ecosystem.To safeguard boreal forest biodiversity and ecosystem functioning, and to maintain the multiple services provided to societies by this forest biome, it is pivotal to maintain an adequate share and the ecological qualities of young postdisturbance stages, along with mature forest stages with old-growth characteristics. This requires management for natural post-disturbance legacy structures, and innovative use of diverse uneven-aged and continuous cover management approaches to maintain critical late-successional forest structures in landscapes.

Empirical evaluation of confidence and prediction intervals for spatial models of forest structure in Jalisco,Mexico

In recent years there has been an increasing interest in developing spatial statistical models for data sets that are seemingly spatially independent.This lack of spatial structure makes it difficult,if not impossible to use optimal predictors such as ordinary kriging for modeling the spatial variability in the data.In many instances,the data still contain a wealth of information that could be used to gain flexibility and precision in estimation.In this paper we propose using a combination of regression analysis to describe the large-scale spatial variability in a set of survey data and a tree-based stratification design to enhance the estimation process of the small-scale spatial variability.With this approach,sample units（i.e.,pixel of a satellite image） are classified with respect to predictions of error attributes into homogeneous classes,and the classes are then used as strata in the stratified analysis.Independent variables used as a basis of stratification included terrain data and satellite imagery.A decision rule was used to identify a tree size that minimized the error in estimating the variance of the mean response and prediction uncertainties at new spatial locations.This approach was applied to a set of n=937 forested plots from a state-wide inventory conducted in 2006 in the Mexican State of Jalisco.The final models accounted for 62% to 82% of the variability observed in canopy closure（%）,basal area（m2·ha-1）,cubic volumes（m3·ha-1） and biomass（t·ha-1） on the sample plots.The spatial models provided unbiased estimates and when averaged over all sample units in the population,estimates of forest structure were very close to those obtained using classical estimates based on the sampling strategy used in the state-wide inventory.The spatial models also provided unbiased estimates of model variances leading to confidence and prediction coverage rates close to the 0.95 nominal rate.

Fuel characteristics, loads and consumption in Scots pine forests of central Siberia

Forest fuel investigations in central and southern Siberian taiga of Scots pine forest stands dominated by lichen and feather moss ground vegetation cover revealed that total aboveground biomass varied from 13.1 to 21.0 kg/m 2.Stand biomass was higher in plots in the southern taiga,while ground fuel loads were higher in the central taiga.We developed equations for fuel biomass(both aerial and ground)that could be applicable to similar pine forest sites of Central Siberia.Fuel loading variability found among plots is related to the impact and recovery time since the last wildfi re and the mosaic distribution of living vegetation.Fuel consumption due to surface fi res of low to high-intensities ranged from 0.95 to 3.08 kg/m 2,that is,18–74%from prefi re values.The total amount of fuels available to burn in case of fi re was up to 4.5–6.5 kg/m 2.Moisture content of fuels(litter,lichen,feather moss)was related to weather conditions characterized by the Russian Fire Danger Index(PV-1)and FWI code of the Canadian Forest Fire Weather Index System.The data obtained provide a strong foundation for understanding and modeling fi re behavior,emissions,and fi re eff ects on ecosystem processes and carbon stocks and could be used to improve existing global and regional models that incorporate biomass and fuel characteristics.

Spatiotemporal variation in forest fire danger from 1996 to 2010 in Jilin Province,China

We evaluated the spatial and temporal patterns of forest fires in two fire seasons (March to June and September to November) from 1996 to 2010 in Jilin Province, China, using the Canadian Forest Fire Weather Index System. Fire data were obtained from the Provincial Fire Agency, and historical climate records of daily weather observations were collected from 36 weather stations in Jilin and its neighboring provinces. A linear regression model was used to analyze linear trends between climate and fire weather indices with time treated as an independent variable. Correlation analysis was used to detect correlations between fire frequency, areas burned, and fire weather indices. A thin-plate smooth spline model was used to interpolate the point data of 36 weather stations to generate a surface covering the whole province. Our analyses indicated fire frequency and areas burned were significantly correlated with fire weather indices. Overall, the Canadian Forest Fire Weather Index System appeared to be work well for determining the fire danger rating in Jilin Province. Also, our analyses indicated that in the forthcoming decades, the overall fire danger in March and April should decrease across the province, but the chance of a large fire in these months would increase. The fire danger in the fall fire season would increase in the future, and the chance of large fire would also increase. Historically, because most fires have occurred in the spring in Jilin Province, such a shift in the future fire danger between the two fire seasons would be beneficial for the province's fire management.

Forest biodiversity, relationships to structural and functional attributes, and stability in New England forests

Background： Forest biodiversity is the foundation of many ecosystem services, and the effect of biodiversity on ecosystem functioning and processes （BEF） has been a central issue in biodiversity studies. Although many hypotheses have been developed to interpret global gradients of biodiversity, there has not been complete agreement on mechanisms controlling biodiversity patterns and distributions. Differences may be due to limited observation data and inconsistencies of spatial scales in analysis. Methods： In this study, we take advantage of USDA Forest Service forest inventory and analysis （FIA） data for exploring regional forest biodiversity and BEF in New England forests. The FIA data provide detailed information of sampled plots and trees for the region, including 6000 FIA plots and more than 33,000 individual trees. Biodiversity models were used to analyze the data. Results： Tree species diversity increases from the north to the south at a rate about 2-3 species per latitudinal degree. Tree species diversity is better predicted by tree height than forest age or biomass. Very different distribution patterns of two common maple species, sugar maple （Acer sdcchorum） and red maple （Acer rubrum）, highlight the vulnerability of sugar maple and its potential replacement by red maple on New England landscapes. Red maple generally already outperforms sugar maple, and will likely and continuously benefit from a changing climate in New England. Conclusions： We conclude that forest structure （height） and resources （biomass） are more likely foundational characteristics supporting biodiversity rather than biodiversity determining forest productivity and/or biomass. The potential replacement of red maple for sugar maple in the New England areas could affect biodiversity and stability of forest ecosystem functioning because sugar maple plays important ecological roles distinct from red maple that are beneficial to other tree species in northern hardwood forests. Such a change may not affect forest resilience in terms of forest productivity and biomass as these are similar in red maple and sugar maple, however, it would almost certainly alter forest structure across the landscape.

Predicting Ailanthus altissima presence across a managed forest landscape in southeast Ohio

Background: The negative impacts of the exotic tree, Ailanthus altissima(tree-of-heaven, stink tree), is spreading throughout much of the Eastern United States. When forests are disturbed, it can invade and expand quickly if seed sources are nearby.Methods: We conducted studies at the highly dissected Tar Hollow State Forest(THSF) in southeastern Ohio USA,where Ailanthus is widely distributed within the forest, harvests have been ongoing for decades, and prescribed fire had been applied to about a quarter of the study area. Our intention was to develop models to evaluate the relationship of Ailanthus presence to prescribed fire, harvesting activity, and other landscape characteristics, using this Ohio location as a case study. Field assessments of the demography of Ailanthus and other stand attributes(e.g., fire, harvesting, stand structure) were conducted on 267 sample plots on a 400-m grid throughout THSF,supplemented by identification of Ailanthus seed-sources via digital aerial sketch mapping during the dormant season. Statistical modeling tools Random Forest(RF), Classification and Regression Trees(CART), and Maxent were used to assess relationships among attributes, then model habitats suitable for Ailanthus presence.Results: In all, 41 variables were considered in the models, including variables related to management activities, soil characteristics, topography, and vegetation structure(derived from LiDAR). The most important predictor of Ailanthus presence was some measure of recent timber harvest, either mapped harvest history(CART) or LiDARderived canopy height(Maxent). Importantly, neither prescribed fire or soil variables appeared as important predictors of Ailanthus presence or absence in any of the models of the THSF.Conclusions: These modeling techniques provide tools and methodologies for assessing landscapes for Ailanthus invasion, as well as those areas with higher potentials for invasion should seed sources become available. Though a case study on an Ohio forest, these tools can be modified for use anywhere Ailanthus is invading.

Comparison of litterfall production in three forest types in Jeju Island, South Korea

Litterfall, which is influenced by physical and biological factors, is a major pathway for carbon and nutrient cycling in forest ecosystems. The purpose of this study was to investigate monthly litterfall production in three forests in Jeju Island differentiated by forest composition and precipitation: Cheongsu(Quercus glauca as the dominant species;low precipitation), Seonheulb(Q. glauca as the dominant species;high precipitation), and Seonheulm(Q. glauca and Pinus thunbergii as the dominant species;high precipitation). Litterfall was collected monthly from April to December 2015 and divided into leaf litter, twig, bark, seeds, and unidentified materials.Seasonal patterns of litterfall production varied across stands according to their species composition. However,the amount of leaf litterfall and total litterfall were comparable among stands, ranging from 362 to 375 g m-2 for leaf litter and 524 g m-2 to 580 g m-2 for total litterfall.Oak leaf litter in May was the highest in all stands, while needle litter was the highest in December in Seonheulm.High twig litterfall in July may be attributable to high rainfall with strong winds and storms during the rainy season. Although forest type and climate factor had no influence on litterfall amounts in this study, the pattern of litterfall production was species dependent, suggesting diverse effects on carbon and nutrient cycling in these forests.

Forest structure and woody plant species composition after a wildfire in beech forests in the north of Iran

Beech （Fagus orientalis Lipsky） forest covers about 565,000 ha of land in Guilan province, north of Iran and forms a major carbon pool. It is an important economic, soil protection and recreation resource. We studied long-term effects of fire on the structure and composition 37 years after fire occurrence in these forests. To do this research, we selected 85 ha burned and 85 ha unburned beech forests）. The results indicated that the fire had not changed the overall uneven-aged structure, but it changed forest composition from pure stands to mixed stands that now include species such as Carpinus betulus, Acer cappadocicum and Alnus subcordata. The density of trees and regeneration was significantly increased, while the density of shrubs significantly decreased. The main reasons for increased tree regeneration were attributed to （1） reduction of litter depth, and （2） increase in available light from opening of the canopy and reduction in shrub competition. It is apparent that the forest is on a path to return to its natural state before the fire after 37 years.