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

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

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

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

Improved modeling and analysis of the patch size–frequency distribution of forest disturbances in China based on a Landsat forest cover change product

Forest disturbances have been altering the ecological properties of ecosystems;meanwhile,disturbance events of varying sizes create different structures and functions for a forest landscape.Therefore,size and frequency are important attributes of disturbances,and their relationship should be studied.We present a hierarchical method through the modeling of the overall trend of the size–frequency distribution and the characterization of the non-constant variances of disturbance sizes at each frequency level.This method was demonstrated to accurately model the sizes as well as the corresponding frequencies;thus,the total disturbed area and number of disturbance patches were both accurately estimated.By applying the method to 13 provinces in China,consistent patterns were revealed by the modeling results and remote-sensing-based product,showing that between 2000 and 2005,forests in most provinces were dominated by moderate disturbances(10 ha<size<100 ha).Southeastern provinces contain the largest proportion of small disturbances(size<10 ha),whereas most of the very large disturbances(size>1000 ha)occurred in the northeastern and northwestern provinces.This study concludes that the proposed method can improve the representation of the size–frequency distribution of forest disturbances.

Sand mining disturbances and their effects on the diversity of arbuscular mycorrhizal fungi in a riparian forest of Iran

The major objective of this study was to evaluate the effects of sand mining disturbances on the diversity of arbuscular mycorrhizal fungi（AMF）. In addition, the proportional changes in the diversity of AMF to the distances from riverbanks were assessed. For this purpose, the riparian forest of the Maroon River, Iran was divided into three locations with a 200-meter wide zone in between. Thus, the locations studied were named Distance I（riverbank）, Distance II（intermediate）, and Distance III（farthest from riverbank）. In each of these distances, 10 Tamarix arceuthoides and Populus euphratica of each species were randomly selected. At the same time, soil and root samples were collected from the rhizosphere of the tree species studied. Results indicated that totally 13 AMF species were observed in T. arceuthoides and 19 AMF species were recorded in P. euphratica rhizosphere belonging to 6 genera and 6 families. In these AMF species, Glomus segmentatum, G. geosporum, G. rubiforme, G. nanolumen, G. spinuliferum, Claroideoglomus drummondii, Gigaspora gigantea and Acaulospora paulinae appeared only in P. euphratica rhizosphere, while G. multiforum and Claroideoglomus claroideum were observed only in T. arceuthoides rhizosphere. Moreover, Distance II had the least AMF species both in T. arceuthoides and in P. euphratica rhizospheres, and also the least spore density and root colonization rate. Our results are important in that they provide a list of resistant AMF species that could be used in the conservation of biodiversity.

Remote Sensing and Forest Carbon Monitoring——a Review of Recent Progress,Challenges and Opportunities

Remote sensing provides key inputs to a wide range of models and methods developed for quantifying forest carbon.In particular,carbon inventory methods recommended by IPCC require biomass data and a suite of forest disturbance products.Significant progress has been made in deriving these products by leveraging publicly available remote sensing assets,including observations acquired by the legendary Landsat mission and new systems launched within the past decade,including Sentinel-2,Sentinel-1,GEDI,and ICESAT-2.With the L-band NISAR and P-band BIOMASS missions to be launched in 2023,the Earth’s land surfaces will be imaged by optical and multi-band(including C-,L-,and P-bands)radar systems that can provide global,sub-weekly observations at sub-hectare spatial resolutions for public use.Fine scale products derived from these observations will be crucial for developing monitoring,reporting,and verification(MRV)capabilities needed to support carbon trade,REDD+,and other market-driven tools aimed at achieving climate mitigation goals through forest management at all levels.Following a brief discussion of the roles of forests in the global carbon cycle and the wide range of models and methods available for evaluating forest carbon dynamics,this paper provides an overview of recent progress and forthcoming opportunities in using remote sensing to map forest structure and biomass,detect forest disturbances,determine disturbance attribution,quantify disturbance intensity,and estimate harvested timber volume.Advances in these research areas require large quantities of well—distributed reference data to calibrate remote sensing algorithms and to validate the derived products.In addition,two of the forest carbon pools-dead organic matter and soil carbon—are difficult to monitor using modern remote sensing capabilities.Carefully designed inventory programs are needed to collect the required reference data as well as the data needed to estimate dead organic matter and soil carbon.

Characterizing long-term forest disturbance history and its drivers in the Ning-Zhen Mountains, Jiangsu Province of eastern China using yearly Landsat observations (1987–2011)

Forest losses or gains have long been recognized as critical processes modulating the carbon flux between the biosphere and the atmosphere. Timely, accurate and spatially explicit information on forest disturbance and recovery history is required for assessing the effectiveness of existing forest management. The major objectives of our research focused on testing the mapping efficacy of the vegetation change tracker （VCT） model over a forested area in China. We used a new version of VCT algorithm built upon the Landsat time series stacks （LTSS）. The LTSS consisted of yearly image acquisitions to map forest disturbance history from 1987 to 2011 over the Ning-Zhen Mountains, Jiangsu Province of east China. The LTSS consisted of TM and ETM＋ scenes with different projec- tions due to distinct data sources （Beijing remote sensing ground station and the USGS EROS Center）. The valida- tion results of the disturbance year maps showed that most spatial agreement measures ranged from 70 to 86 %, comparable with the VCT accuracies reported for many places in USA. Very low accuracies were identified in 1995 （38.3 %） and 1992 （56.2 %） in the current analysis. These resulted from the insensitivity of the VCT algorithm to detect low intensity disturbances and also from the mis- registration errors of the image pairs. Major forest distur- bance types existing in our study area were identified as agricultural expansion （39.8 %）, urbanization （24.9 %）, forest management practice （19.3 %）, and mining （12.8 %）. In general, there was a gradual decreasing trend in forest cover throughout this region, caused principally by China＇s economic, demographic, environmental and political policies and decisions, as well as some weather events. While VCT has largely been used to assess long term changes and trends in the USA, it has great potential for assessing landscape level change elsewhere throughout the world.

Carbon sequestration in Chir-Pine(Pinus roxburghii Sarg.) forests under various disturbance levels in Kumaun Central Himalaya

We studied variations in tree biomass and carbon sequestration rates of Chir Pine （Pinus roxburghii. Sarg.） forest in three categories of forest disturbance, protected, moderately disturbed, and highly disturbed. In the first year, total biomass was 14.7.t.ha-1 in highly disturbed site, 94.46 t.ha-1 in moderately disturbed forest, and 112.0 t.ha-1 in protected forest. The soil organic carbon in the top 20 cm of soil ranged from 0.63 to 1.2%. The total rate of carbon sequestration was 0.60 （t/ha）.a-lon the highly disturbed site, 1.03 （t/ha）a-1 on the moderately disturbed site, and 4.3 （t/ha）.a-1 on the protectedsite. Keywords： carbon sequestration, soil organic carbon （SOC）, disturbed forest, vegetation analysis, allometric equations

Spatio-temporal Variations in Plantation Forests'Disturbance and Recovery of Northern Guangdong Province Using Yearly Landsat Time Series Observations(1986-2015)

Forest disturbance plays a vital role in modulating carbon storage,biodiversity and climate change.Yearly Landsat imagery from 1986 to 2015 of a typical plantation region in the northern Guangdong province of southern China was used as a case study.A Landsat time series stack(LTSS) was fed to the vegetation change tracker model(VCT) to map long-term changes in plantation forests' disturbance and recovery,followed by an intensive validation and a continuous 27-yr change analysis on disturbance locations,magnitudes and rates of plantations' disturbance and recovery.And the validation results of the disturbance year maps derived from five randomly identified sample plots with 25 km^2 located at the four corners and the center of the scene showed the majority of the spatial agreement measures ranged from 60% to 83%.A confusion matrix summary of the accuracy measures for all four validation sites in Fogang County showed that the disturbance year maps had an overall accuracy estimate of 71.70%.Forest disturbance rates' change trend was characterized by a decline first,followed by an increase,then giving way to a decline again.An undulated and gentle decreasing trend of disturbance rates from the highest value of 3.95% to the lowest value of 0.76% occurred between 1988 and 2001,disturbance rate of 4.51% in 1994 was a notable anomaly,while after 2001 there was a sharp ascending change,forest disturbance rate spiked in 2007(5.84%).After that,there was a significant decreasing trend up to the lowest value of 1.96% in 2011 and a slight ascending trend from 2011 to 2015(2.59%).Two obvious spikes in post-disturbance recovery rates occurred in 1995(0.26%) and 2008(0.41%).Overall,forest recovery rates were lower than forest disturbance rates.Moreover,forest disturbance and recovery detection based on VCT and the Landsat-based detections of trends in disturbance and recovery(LandT rendr) algorithms in Fogang County have been conducted,with LandT rendr finding mostly much more disturbance than VCT.Overall,disturbances and recoveries in northern Guangdong were triggered mostly by timber needs,policies and decisions of the local governments.This study highlights that a better understanding about plantations' changes would provide a critical foundation for local forest management decisions in the southern China.

Conceptual models of forest dynamics in environmental education and management:keep it as simple as possible,but no simpler

Background：Conceptual models of forest dynamics are powerful cognitive tools,which are indispensable for communicating ecological ideas and knowledge,and in developing strategic approaches and setting targets for forest conservation,restoration and sustainable management.Forest development through time is conventionally described as a directional,or ＂linear＂,and predictable sequence of stages from ＂bare ground＂ to old forest representing the ＂climax-state＂.However,this simple view is incompatible with the current knowledge and understanding of intrinsic variability of forest dynamics.Hypothesis：Overly simple conceptual models of forest dynamics easily become transformed into biased mental models of how forests naturally develop and what kind of structures they display.To be able to communicate the essential features and diversity of forest dynamics,comprehensive conceptual models are needed.For this end,Kuuluvainen（2009） suggested a relatively simple conceptual model of forest dynamics,which separates three major modes of forest dynamics,and incorporates state changes and transitions between the forest dynamics modes depending on changes in disturbance regime.Conclusions：Conceptual models of forest dynamics should be comprehensive enough to incorporate both longterm directional change and short-term cyclic forest dynamics,as well as transitions from one dynamics mode to another depending on changes in the driving disturbance regime type.Models that capture such essential features of forest dynamics are indispensable for educational purposes,in setting reference conditions and in developing methods in forest conservation,restoration and ecosystem management.

Effects of Forest Disturbance on Vegetation Structure and Above-Ground Carbon in Three Isolated Forest Patches of Taita Hills

The structure and species composition of undisturbed natural forests serve as benchmarks for understanding forest carbon storage potential for reduced carbon emissions. Even though Kenya is seeking to stabilize forest cover, reverse degradation and increase forest cover through mechanisms such as REDD+, there is relatively little information on inherent forest carbon storage potential or its response to disturbance. Comparative studies were undertaken in three remnant fragments of indigenous forests in Taita Hills, Kenya to characterize the structure and forest carbon storage potential of undisturbed, moderately and heavily disturbed sites within these forests. The sensitivity of forest carbon storage estimates to different methods of tree biomass estimation were also examined, including estimates which used DBH, tree height and wood density from extracted tree cores. Disturbance altered the forest structure, reduced species diversity and decreased the capacity of the forests to sequester carbon. The forests’ capacity to sequester carbon reduced by between 9.2% and 70.7% depending on the site (forest fragment) and level of disturbance. Models with DBH and wood density gave higher quantities of carbon of between 0.9% and 44.4% for sites exhibiting different levels of disturbance. The present results suggest that disturbance had strong influence on forest structure, species diversity and carbon stocks and therefore maintaining the forests’ ecological integrity over the long-term may prove difficult if the frequency and intensity of disturbance increases. Moreover, development and implementation of effective mitigation strategies to reduce carbon emissions will require the use of local biomass models since they are accurate.

Anthropogenic disturbances and their impact on vegetation in Western Himalaya,India

The present study assesses anthropogenic disturbances and their impacts on the vegetation in Western Himalaya,India on the basis of various disturbance parameters such as density,Total Basal Cover(TBC) of cut stumps,lopping percentage and grazing intensities.On the basis of canopy cover and frequency of disturbances(%),the studied forests were divided into highly disturbed(HD),moderately disturbed(MD) and least disturbed(LD) categories.The HD forests had the lowest canopy cover,lowest density and lowest TBC and the LD had the highest canopy cover,highest density and highest TBC.The MD forests occupied the intermediate position with respect to these parameters.Species richness was least in HD forests,highest in one of the MD forests while LD forest occupied an intermediate position.The percentage of regenerating species was lowest(54%) in HD and highest(72%) in MD.The density of seedlings and saplings was higher in one of the MD forests as compared to HD and LD.We concluded that the moderate disturbances do not affect the vegetation adversely;however the increased degree of disturbance causes loss in plant diversity;affects regeneration and changes community characteristics.Construction of hydroelectric projects at various places in the study area was found to be one of the most important sources of anthropogenic disturbances in addition to the routine anthropogenic disturbances like grazing,fuelwood collection and fodder extraction.If all proposed dams in the Indian Himalaya are constructed combined with weak national environmental impact assessment and implementation,it will result in a significant loss of species.Therefore,various agents of disturbances should be evaluated in cumulative manner and any developmental activities such as hydropower projects,which trigger various natural and anthropogenic disturbances,should be combined with proper cumulative environmental impact assessment and effective implementation to minimise the anticipated loss of vegetation.

Influence of climate fluctuations on Pinus palustris growth and drought resilience

The longleaf pine(Pinus palustris Mill.)ecosystem is an endangered ecosystem in the southeastern USA,and efforts to restore the species are ongoing.However,in recent decades,the region has experienced drastic fluctuations between wet and dry growing season conditions from year to year,and it is not fully understood how these fluctuations have influenced the growth of P.palustris.To address this topic,we cored P.palustris trees in woodlands of southwest Georgia and used dendrochronology techniques to determine how climate fluctuations have influenced the growth and drought resilience of P.palustris.We also cored slash pine(Pinus elliottii Engelm.)trees in the same woodlands to compare growth between species.While P.palustris growth was less impacted by adverse climate conditions compared to P.elliottii,the strength of correlations between P.palustris growth and temperature,precipitation,and Palmer Drought Severity Index(PDSI)changed over time.In recent decades,climate conditions during the growing season became more influential on P.palustris growth than the previous year's conditions.This is concerning given that drought severity during the growing season has been increasing.Our results also indicate that P.palustris was less resilient to droughts during the 2000s and 2010s than to those of the 1950s.Under this new climate paradigm,our results suggest that P.palustris might be more susceptible to growth reductions and less resistant to droughts than once expected.This work highlights the importance of understanding the impact of novel climate conditions on P.palustris and has implications for restoration efforts,such as using silvicultural treatments that reduce tree vulnerability to drought(e.g.,thinning)and promote other climate-adapted species in mixture with P.palustris.

Land Use and Environmental Gradients Influence on Riparian Woody Plant Diversity and Structure in Lake Manyara Watershed Ecosystem, Tanzania

Riparian vegetations are important in supporting ecological connectivity between aquatic and terrestrial ecosystems. The structure and species composition of riparian woody plants have been subjected to multiple forces with varying degree of influences. This study examined the influence of land use and environmental gradient to the structure and composition of the riparian woody plants in northern Tanzania. A total of 270 plots were surveyed for woody plant species in the riparian ecosystems and later analysed to determine the influence of land use categories (homegarden, crop field, woodlot, open canopy forest, and closed canopy forest) and environmental variables (temperature, precipitation, elevation and slope) to the species richness, abundance, and stand parameters. Basal area was higher in woodlots, homegardens and crop fields than in the open and closed canopy forests;and as expected the reverse was true for the number of stocking density. Correlation among stand parameters with environmental variables varied significantly. Species richness and species abundance were negatively correlated to precipitation, temperature and elevation, while stocking density and basal area were positively correlated to precipitation. The study recommends continual retentions of trees on farm, further promoting of agroforestry interventions and sustainable utilization of woody plants in open and close canopy forests.

Diversity,population structure and regeneration status of arboreal species in the four sacred groves of Kushalnagar,Karnataka

Assessment of tree species diversity, structure and regeneration status of four sacred groves of Kushalnagar,southern Karnataka was carried out. The random quadrat method was employed in each grove for enumeration of tree diversity and regeneration status. A total of 98 tree species belonging to 38 families were found from the sampled areas.These groves possess higher diversity and basal area. Some67 % of species have shown regeneration, while 17 % of species had no regeneration. Another 15 % of species were reappearing or immigrating. It is observed that increased disturbance was directly proportional to number of reappearing or immigrating species and inversely proportional to the diversity in all the sacred groves. Significant impact on diversity, species richness and regeneration status of the flora due to manifold anthropogenic activities have been recorded.

Characterizing the effects of climate change on short-term post-disturbance forest recovery in southern China from Landsat time-series observations(1988-2016)

Climate change,a recognized critical environmental issue,plays an important role in regulating the structure and function of forest ecosystems by altering forest disturbance and recovery regimes.This research focused on exploring the statistical relationships between meteorological and topographic variables and the recovery characteristics following disturbance of plantation forests in southern China.We used long-term Landsat images and the vegetation change tracker algorithm to map forest disturbance and recovery events in the study area from 1988 to 2016.Stepwise multiple linear regression(MLR),random forest(RF)regression,and support vector machine(SVM)regression were used in conjunction with climate variables and topographic factors to model short-term forest recovery using the normalized difference vegetation index(NDVI).The results demonstrated that the regenerating forests were sensitive to the variation in temperature.The fitted results suggested that the relationship between the NDVI values of the forest areas and the post-disturbance climatic and topographic factors differed in regression algorithms.The RF regression yielded the best performance with an R2 value of 0.7348 for the validation accuracy.This indicated that slope and temperature,especially high temperatures,had substantial effects on post-disturbance vegetation recovery in southern China.For other mid-subtropical monsoon regions with intense light and heat and abundant rainfall,the information will also contribute to appropriate decisions for forest managers on forest recovery measures.Additionally,it is essential to explore the relationships between forest recovery and climate change of different vegetation types or species for more accurate and targeted forest recovery strategies.

An autoencoder-based model for forest disturbance detection using Landsat time series data

Monitoring and classifying disturbed forests can provide information support for not only sustainable forest management but also global carbon sequestration assessments.In this study,we propose an autoencoder-based model for forest disturbance detection,which considers disturbances as anomalous events in forest temporal trajectories.The autoencoder network is established and trained to reconstruct intact forest trajectories.Then,the disturbance detection threshold is derived by Tukey’s method based on the reconstruction error of the intact forest trajectory.The assessment result shows that the model using the NBR time series performs better than the NDVIbased model,with an overall accuracy of 90.3%.The omission and commission errors of disturbed forest are 7%and 12%,respectively.Additionally,the trained NBR-based model is implemented in two test areas,with overall accuracies of 87.2%and 86.1%,indicating the robustness and scalability of the model.Moreover,comparing three common methods,the proposed model performs better,especially for intact forest detection accuracy.This study provides a novel and robust approach with acceptable accuracy for forest disturbance detection,enabling forest disturbance to be identified in regions with limited disturbance reference data.

Potential influence of wildfire in modulating climate-induced forest redistribution in a central Rocky Mountain landscape

Introduction:Climate change is expected to impose significant tension on the geographic distribution of tree species.Yet,tree species range shifts may be delayed by their long life spans,capacity to withstand long periods of physiological stress,and dispersal limitations.Wildfire could theoretically break this biological inertia by killing forest canopies and facilitating species redistribution under changing climate.We investigated the capacity of wildfire to modulate climate-induced tree redistribution across a montane landscape in the central Rocky Mountains under three climate scenarios(contemporary and two warmer future climates)and three wildfire scenarios(representing historical,suppressed,and future fire regimes).Methods:Distributions of four common tree species were projected over 90 years by pairing a climate niche model with a forest landscape simulation model that simulates species dispersal,establishment,and mortality under alternative disturbance regimes and climate scenarios.Results:Three species(Douglas-fir,lodgepole pine,subalpine fir)declined in abundance over time,due to climate-driven contraction in area suitable for establishment,while one species(ponderosa pine)was unable to exploit climate-driven expansion of area suitable for establishment.Increased fire frequency accelerated declines in area occupied by Douglas-fir,lodgepole pine,and subalpine fir,and it maintained local abundance but not range expansion of ponderosa pine.Conclusions:Wildfire may play a larger role in eliminating these conifer species along trailing edges of their distributions than facilitating establishment along leading edges,in part due to dispersal limitations and interspecific competition,and future populations may increasingly depend on persistence in locations unfavorable for their establishment.

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

Using the NASA Earth Exchange platform,the North American Forest Dynamics(NAFD)project mapped forest history wall-to-wall,annually for the contiguous US(1986–2010)using the Vegetation Change Tracker algorithm.As with any effort to identify real changes in remotely sensed time-series,data gaps,shifts in seasonality,misregistration,inconsistent radiometry and cloud contamination can be sources of error.We discuss the NAFD image selection and processing stream(NISPS)that was designed to minimize these sources of error.The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration,unreliability of the pre-2009 L5 cloud cover assessments algorithm,missing growing-season imagery and paucity of clear views.Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study.Over 150,000+Landsat images were considered for the NAFD project.Optimally,one high quality cloud-free image in each year or a total of 12,152 images would be used.However,to accommodate data gaps and cloud/shadow contamination 23,338 images were needed.In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

Species-dependent responses of soil microbial properties to fresh leaf inputs in a subtropical forest soil in South China

Aims Forest disturbance from extreme weather events due to climate change could increase the contribution of fresh green leaves to the litter layer of soil and subsequently alter the composition and activity of the soil microbial properties and soil carbon cycling.The objective of this study was to compare the effect of naturally fallen litter and fresh leaves on the soil microbial community composition and their activities.Methods Fresh leaves and normal fallen litter were collected from four tree species(Pinus elliottii,Schima superba,Acacia mangium,A.auriculaeformis)in subtropical China and mixed with soil.Soil microbial community composition was determined using PLFAs,and its activity was quantified by soil respiration.During a 12-month period,the decomposition rate of litter was measured bimonthly using a litterbag method.Soil microbial samples were collected after 6 and 12 months.Soil respiration was measured monthly.Important Findings We found that fresh leaves decomposed faster than their conspecific fallen litter.Although total microbial biomass and bacterial biomass were similar among treatments,soil fungal biomass was higher in fresh leaf than fallen litter treatments,resulting in greater values of the Fungal phospholipid fatty acids(PLFAs)/Bacterial PLFAs ratio.Fungal PLFA values were greater for Schima superba than the other species.The effect of litter type on soil respiration was species-dependent.Specifically,fallen litter released 35%more CO_(2) than fresh leaves of the conifer P.elliottii.The opposite pattern was observed in the broadleaf species whose fresh leaf treatments emitted 17%–32%more CO_(2) than fallen litter.Given future predictions that global climate change will cause more disturbances to forests,these results indicate that conifer and broadleaf forests in subtropical China may respond differently to increased fresh litter inputs,with net soil microbial respiration decreasing in conifer forests and increasing in broadleaf forests.