Drought events influence nutrient canopy exchanges and green leaf partitioning during senescence in a deciduous forest

The increase in the frequency and intensity of drought events expected in the coming decades in Western Europe may disturb forest biogeochemical cycles and create nutrient deficiencies in trees.One possible origin of nutrient deficiency is the disturbance of the partitioning of the green leaf pool during the leaf senescence period between resorption,foliar leaching and senesced leaves.However,the effects of drought events on this partitioning and the consequences for the maintenance of tree nutrition are poorly documented.An experiment in a beech forest in Meuse(France)was conducted to assess the effect of drought events on nutrient canopy exchanges and on the partitioning of the green leaf pool during the leaf senescence period.The aim was to identify potential nutritional consequences of droughts for trees.Monitoring nutrient dynamics,including resorption,chemistry of green and senesced leaves,foliar absorption and leaching in mature beech stands from 2012 to 2019 allowed us to compare the nutrient exchanges for three nondry and three dry years(i.e.,with an intense drought event during the growing season).During dry years,we observed a decrease by almost a third of the potassium(K)partitioning to resorption(i.e.resorption efficiency),thus reducing the K reserve in trees for the next growing season.This result suggests that with the increased drought frequency and intensity expected for the coming decades,there will be a risk of potassium deficiency in trees,as already observed in a rainfall exclusion experiment on the same study site.Reduced foliar leaching and higher parititioning to the senesced leaves for K and phosphorus(P)were also observed.In addition,a slight increase in nitrogen(N)resorption efficiency occurred during dry years which is more likely to improve tree nutrition.The calcium(Ca)negative resorption decreased,with no apparent consequence in our study site.Our results show that nutrient exchanges in the canopy and the partitioning of the green leaf pool can be modified by drought events,and may have consequences on tree nutrition.

Determination of the Pile Drivability Using Random Forest Optimized by Particle Swarm Optimization and Bayesian Optimizer

Driven piles are used in many geological environments as a practical and convenient structural component.Hence,the determination of the drivability of piles is actually of great importance in complex geotechnical applications.Conventional methods of predicting pile drivability often rely on simplified physicalmodels or empirical formulas,whichmay lack accuracy or applicability in complex geological conditions.Therefore,this study presents a practical machine learning approach,namely a Random Forest(RF)optimized by Bayesian Optimization(BO)and Particle Swarm Optimization(PSO),which not only enhances prediction accuracy but also better adapts to varying geological environments to predict the drivability parameters of piles(i.e.,maximumcompressive stress,maximum tensile stress,and blow per foot).In addition,support vector regression,extreme gradient boosting,k nearest neighbor,and decision tree are also used and applied for comparison purposes.In order to train and test these models,among the 4072 datasets collected with 17model inputs,3258 datasets were randomly selected for training,and the remaining 814 datasets were used for model testing.Lastly,the results of these models were compared and evaluated using two performance indices,i.e.,the root mean square error(RMSE)and the coefficient of determination(R2).The results indicate that the optimized RF model achieved lower RMSE than other prediction models in predicting the three parameters,specifically 0.044,0.438,and 0.146;and higher R^(2) values than other implemented techniques,specifically 0.966,0.884,and 0.977.In addition,the sensitivity and uncertainty of the optimized RF model were analyzed using Sobol sensitivity analysis and Monte Carlo(MC)simulation.It can be concluded that the optimized RF model could be used to predict the performance of the pile,and it may provide a useful reference for solving some problems under similar engineering conditions.

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

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

Satellite remote sensing reveals overwhelming recovery of forest from disturbances in Asia

Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability of forests.At the same time,detailed accounts of disturbances and forest responses are not yet well quantified in Asia.This study employed the Breaks For Additive Seasonal and Trend method-an abrupt-change detection method-to analyze the Enhanced Vegetation Index time series in East Asia,South Asia,and Southeast Asia.This approach allowed us to detect forest disturbance and quantify the resilience after disturbance.Results showed that 20%of forests experienced disturbance with an increasing trend from 2000 to 2022,and Southeast Asian countries were more severely affected by disturbances.Specifically,95%of forests had robust resilience and could recover from disturbance within a few decades.The resilience of forests suffering from greater magnitude of disturbance tended to be stronger than forests with lower disturbance magnitude.In summary,this study investigated the resilience of forests across the low and middle latitudes of Asia over the past two decades.The authors found that most forests exhibited good resilience after disturbance and about two-thirds had recovered to a better state in 2022.The findings of this study underscore the complex relationship between disturbance and resilience,contributing to comprehension of forest resilience through satellite remote sensing.

Canopy structural heterogeneity drivesαandβspeciesegenetic diversity correlations in a Chinese subtropical forest

Patterns and drivers of species–genetic diversity correlations(SGDCs)have been broadly examined across taxa and ecosystems and greatly deepen our understanding of how biodiversity is maintained.However,few studies have examined the role of canopy structural heterogeneity,which is a defining feature of forests,in shaping SGDCs.Here,we determine what factors contribute toα-andβ-species–genetic diversity correlations(i.e.,α-andβ-SGDCs)in a Chinese subtropical forest.For this purpose,we used neutral molecular markers to assess genetic variation in almost all adult individuals of the dominant tree species,Lithocarpus xylocarpus,across plots in the Ailaoshan National Natural Reserve.We also quantified microhabitat variation by quantifying canopy structure heterogeneity with airborne laser scanning on 201-ha subtropical forest plots.We found that speciesα-diversity was negatively correlated with geneticα-diversity.Canopy structural heterogeneity was positively correlated with speciesα-diversity but negatively correlated with geneticα-diversity.These contrasting effects contributed to the formation of a negativeα-SGDC.Further,we found that canopy structural heterogeneity increases speciesα-diversity and decreases geneticα-diversity by reducing the population size of target species.Speciesβ-diversity,in contrast,was positively correlated with geneticβ-diversity.Differences in canopy structural heterogeneity between plots had non-linear parallel effects on the two levels ofβ-diversity,while geographic distance had a relatively weak effect onβ-SGDC.Our study indicates that canopy structural heterogeneity simultaneously affects plot-level community species diversity and population genetic diversity,and species and genetic turnover across plots,thus drivingα-andβ-SGDCs.

Modeling of Spring Phenology of Boreal Forest by Coupling Machine Learning and Diurnal Temperature Indicators

The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.

Heterogeneous occurrence of evergreen broad-leaved forests in East Asia:Evidence from plant fossils

Evergreen broad-leaved forests(EBLFs)are widely distributed in East Asia and play a vital role in ecosystem stability.The occurrence of these forests in East Asia has been a subject of debate across various disciplines.In this study,we explored the occurrence of East Asian EBLFs from a paleobotanical perspective.By collecting plant fossils from four regions in East Asia,we have established the evolutionary history of EBLFs.Through floral similarity analysis and paleoclimatic reconstruction,we have revealed a diverse spatio-temporal pattern for the occurrence of EBLFs in East Asia.The earliest occurrence of EBLFs in southern China can be traced back to the middle Eocene,followed by southwestern China during the late Eoceneeearly Oligocene.Subsequently,EBLFs emerged in Japan during the early Oligocene and eventually appeared in central-eastern China around the Miocene.Paleoclimate simulation results suggest that the precipitation of wettest quarter(PWetQ,mm)exceeding 600 mm is crucial for the occurrence of EBLFs.Furthermore,the heterogeneous occurrence of EBLFs in East Asia is closely associated with the evolution of the Asian Monsoon.This study provides new insights into the occurrence of EBLFs in East Asia.

Latitudinal patterns of tree b-diversity and relevant ecological processes vary across spatial extents in forests of southeastern China

Latitudinal patterns of treeβ-diversity reveal important insights into the biogeographical processes that influence forest ecosystems.Although previous studies have extensively documentedβ-diversity within relatively small spatial extents,the potential drivers ofβ-diversity along latitudinal gradients are still not well understood at larger spatial extents.In this study,we determined whether treeβ-diversity is correlated with latitude in forests of southeastern China,and if so,what ecological processes contribute to these patterns of treeβ-diversity.We specifically aimed to disentangle the relative contributions from interspecific aggregation and environmental filtering across various spatial extents.We delineated regional communities comprising multiple nearby national forest inventory(NFI)plots around random focal plots.The number of NFI plots in a regional community served as a surrogate for spatial extent.We also used a null model to simulate randomly assembled communities and quantify the deviation(β-deviation)between observed and expectedβ-diversity.We found thatβ-diversity decreased along a latitudinal gradient and that this pattern was clearer at larger spatial extents.In addition,latitudinal patterns ofβ-deviation were explained by the degree of species spatial aggregation.We also identified environmental factors that driveβ-deviation in these forests,including precipitation,seasonality,and temperature variation.At larger spatial extents,these environmental variables explained up to 84%of theβ-deviation.Our results reinforce that ecological processes are scale-dependent and collectively contribute to theβ-gradient in subtropical forests.We recommend that conservation efforts maintain diverse forests and heterogeneous environments at multiple spatial extents to mitigate the adverse effects of climate change.

Light Use Efficiency Model Based on Chlorophyll Content Better Captures Seasonal Gross Primary Production Dynamics of Deciduous Broadleaf Forests

Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.

基于Deep Forest算法的对虾急性肝胰腺坏死病(AHPND)预警数学模型构建

为预报池塘养殖凡纳对虾(Penaeus vannamei)急性肝胰腺坏死病(AHPND)的发生,自2020年开始,笔者对凡纳对虾养殖区开展了连续监测工作,包括与疾病发生相关的环境理化因子、微生物因子、虾体自身健康状况等18个候选预警因子指标,通过数据标准化处理后分析病原、宿主与环境之间的相关性,对候选预警因子进行筛选,基于Python语言编程结合Deep Forest、Light GBM、XGBoost算法进行数据建模和预测性能评判,仿真环境为Python2.7,以预警因子指标作为输入样本(即警兆),以对虾是否发病指标作为输出结果(即警情),根据输入样本和输出结果各自建立输入数据矩阵和目标数据矩阵,利用原始数据矩阵对输入样本进行初始化,结合函数方程进行拟合,拟合的源代码能利用已知环境、病原及对虾免疫指标数据对目标警情进行预测。最终建立了基于Deep Forest算法的虾体(肝胰腺内)细菌总数、虾体弧菌(Vibrio)占比、水体细菌总数和盐度的4维向量预警预报模型,准确率达89.00%。本研究将人工智能算法应用到对虾AHPND发生的预测预报,相关研究结果为对虾AHPND疾病预警预报建立了预警数学模型,并为对虾健康养殖和疾病防控提供了技术支撑和有力保障。

Forest fire risk assessment in parts of Northeast India using geospatial tools

Forest fire is a major cause of changes in forest structure and function. Among various floristic regions, the northeast region of India suffers maximum from the fires due to age-old practice of shifting cultivation and spread of fires from jhum fields. For proper mitigation and management, an early warning of forest fires through risk modeling is required. The study results demonstrate the potential use of remote sensing and Geographic Information System （GIS） in identifying forest fire prone areas in Manipur, southeastern part of Northeast India. Land use land cover （LULC）, vegetation type, Digital elevation model （DEM）, slope, aspect and proximity to roads and settlements, factors that influence the behavior of fire, were used to model the forest fire risk zones. Each class of the layers was given weight according to their fire inducing capability and their sensitivity to fire. Weighted sum modeling and ISODATA clustering was used to classify the fire zones. TO validate the results, Along Track Scanning Radiometer （ATSR）, the historical fire hotspots data was used to check the occurrence points and modeled forest fire locations. The forest risk zone map has 55-63% of agreement with ATSR dataset.

Optimal Control of Slurry Pressure during Shield Tunnelling Based on Random Forest and Particle Swarm Optimization

The control of slurry pressure aiming to be consistent with the external water and earth pressure during shield tunnelling has great significance for face stability,especially in urban areas or underwater where the surrounding environment is very sensitive to the fluctuation of slurry pressure.In this study,an optimal control method for slurry pressure during shield tunnelling is developed,which is composed of an identifier and a controller.The established identifier based on the random forest(RF)can describe the complex non-linear relationship between slurry pressure and its influencing factors.The proposed controller based on particle swarm optimization(PSO)can optimize the key factor to precisely control the slurry pressure at the normal state of advancement.A data set from Tsinghua Yuan Tunnel in China was used to train the RF model and several performance measures like R2,RMSE,etc.,were employed to evaluate.Then,the hybrid RF-PSO control method is adopted to optimize the control of slurry pressure.The good agreement between optimized slurry pressure and expected values demonstrates a high identifying and control precision.

Economic contribution of participatory agroforestry program to poverty alleviation: a case from Sal forests, Bangladesh

In the Forest Department of Bangladesh, a Participatory Agroforestry Program （PAP） was initiated at a denuded Sal forests area to protect the forest resources and to alleviate poverty amongst the local poor population. We explored whether the PAP reduced poverty and what factors might be responsible for poverty alleviation. We used three poverty measurement methods： the Head Count Index, the Poverty Gap Index and the Foster-Greer-Thorbecke index to determine the extent poverty reduction. We used a linear regression model to determine the possible differences among factors in poverty reduction. Data were collected through semi structured questionnaires and face to face interviews within the study area. PAP proved effective at poverty alleviation, considerably improving the local situation. The linear regression model showed that PAP output explained the income differences in poverty reduction. Participants identified bureaucracy and illegal money demands by forest department officials, an uncontrolled market system, and underdeveloped road infrastructure as the main obstacles to reduction of poverty. Overall, PAP is quite successful in alleviating poverty. So this program might be of interest at other degraded forest areas as a tool to alleviate poverty.

Assessment of soil erodibility and aggregate stability for different parts of a forest road

We measured erodibility and mean weight diameter （MWD） of soil aggregates in different parts of a forest road. Samples of topsoil were collected from cutslope, fillslope, road surface and forest ground to assess the texture, bulk density, moisture, CaCO3 and organic matter. Soil aggregate stability was determined by wet sieving. Soil erodibility on the road surface was 2.3 and 1.3 times higher than on the fillslope and cutslope, respectively. The forest soil had the lowest erodibility. Aggregate stability of cutslope and road surface were low and very low, respectively. There was a significant negative relationship between cutslope erodibility with CaCO3 and sand content. Cutslope erodibility increased with increasing silt, clay and moisture content. On fillslopes, MWD increased with in-creasing rock fragment cover, plant cover, litter cover, organic matter and sand. There was a strong negative correlation between fillslope erodibility and organic matter, sand and MWD. There was no significant difference between erodibility of bare soil and soils beneathRubus hyrcanusL. and Philonotis marchica （Hedw.） Brid.

Community Participation in Forest Resource Management in Nepal

Livelihood of the people in Nepal hills depends much upon forest resources in addition to farming as forest plays a critical role in the well being of the farming households where access to alternative sources, such as energy for cooking, nutrition for animals, materials for fertilizer and constructing materials for shelter, are limited. Thus, the well being of the people in the hills is directly affected by the management of these forest resources. This issue was addressed in this paper by examining the forest resource management practices and its effect on well being of rural people in two different stages in a village lying in the steep hill of Mahabharat Range in the southern hills of Kathmandu valley, Lalitpur District. The main ethnic/caste groups in the village are Brahmin/Chhetri (high Hindu caste), Magar/Tamang (Tibeto Burmans) and Kami (occupational caste: cobbler). Currently there are four community forest users groups, with mixed ethnic membership, organized to manage the forest resources. The endowments, weak institutional settings, before 1990 helped the Bhramins, Magars and Tamangs to get access into the private forest endowment, which made them easy to get access to the forest resources, mainly fuel wood, fodder and timber in 1990 and enhanced their well beings. But the socially backward Kami could not get benefit from the institutions that existed during that time and had less chance to enhance their well beings. After the set up of different endowments during late 1990s, i.e., hand over of forest management to usersgroupsin line with the concept of community forest, environment to use the forest resources became better for all the groups, along with the management of the forest. This enhanced the well beings of all the groups in the study village. However, the ability of Kami to use the forest resources to enhance their well beings was still lacking behind. The reason was partially due to the difference in endowments carried over from the endowments before 1990, and partly due to their occupational work and location of their settlements.

A pattern for partnership between LMDH and Perhutani to enhance local community prosperity and preserve the forest:a case study at RPH Besowo,Kediri Regency,Indonesia

The deforestation in Indonesia is already alarming.One of the strategies used by the government to overcome forest deforestation is social forestry.This program is called PHBM(Pengelolaan Hutan Bersama Masyarakat/Joint Forest Management) which is basically a partnership program.This study aims at describing the partnership program between a local organization(i.e.LMDH) and a government unit(i.e.RPH of Perhutani) within the PHBM program.The objectives of this study are to(a) describe the model of partnerships between LMDH and RPH Besowo for sustainable forest management and local community empowerment;(b) determine the contribution of the forest to the national economy and rural household income;and(c) determine the obstacles commonly found in Besowo forest that have to be faced during the implementation of the partnerships.The study shows that with good partnership between these two units,the prosperity of the local community can be enhanced and the forest preservation can be maintained.The model of the partnerships in this particular area in Indonesia is expected to be applicable as well in other rural areas in Indonesia,as well as in other developing countries.

Forest management causes soil carbon loss by reducing particulate organic carbon in Guangxi, Southern China

Background: The loss of soil organic carbon(SOC) following conversion of natural forests to managed plantations has been widely reported. However, how different SOC fractions and microbial necromass C(MNC) respond to forest management practices remains unclear.Methods: We sampled 0–10 cm mineral soil from three different management plantations and one protected forest in Guangxi, Southern China, to explore how forest management practices affect SOC through changing mineralassociated C(MAOC) and particulate organic C(POC), as well as fungal and bacterial necromass C.Results: Compared with the protected forest, SOC and POC in the abandoned, mixed and Eucalyptus plantations significantly decreased, but MAOC showed no significant change, indicating that the loss of SOC was mainly from decreased POC under forest management. Forest management also significantly reduced root biomass, soil extractable organic C, MNC, and total microbial biomass(measured by phospholipid fatty acid), but increased fungi-to-bacteria ratio(F:B) and soil peroxidase activity. Moreover, POC was positively correlated with root biomass, total microbial biomass and MNC, and negatively with F:B and peroxidase activity. These results suggested that root input and microbial properties together regulated soil POC dynamics during forest management.Conclusion: Overall, this study indicates that forest management intervention significantly decreases SOC by reducing POC in Guangxi, Southern China, and suggests that forest protection can help to sequester more soil C in forest ecosystems.

Runoff and sediment concentration of different parts of a road in Hyrcanian forests

Road prisms, such as cutslopes, fillslopes and road surfaces, can be important contributors of sediment to streams in forested watersheds. In this study rainfall simulations were carried out on cutslopes, fillslopes, road surfaces and forest grounds in hardwood forests of Lolet and Lat Talar, Iran. Water at intensity of 32.4 mm·h-1 was sprayed from a nozzle onto a square area of 0.48 m2. Runoff was collected by water gauge every 4 min and then runoff and sediment parameters were measured in each plot. Results indicated that on road surfaces, the runoff coefficient was 63.28%. On the cutslopes and fillslopes, the runoff coefficients were 35.14% and 10.23%, respectively. On the forest ground as a control, the runoff coefficient was 5.90%. Runoff volume was 2.73 mL·s^-1 on the road surfaces and 1.52 mL·s^-1 on cutslopes. On fillslopes the runoff volume was 0.44 mL·s^-1 and on the forest ground 0.25 mL·s^-1 The greatest rate of soil loss was found on the cutslope （280.79 g·m-2·h-1）. The total soil loss from the cutslopes was two times higher than that from the road surfaces and six times higher than that from the fillslopes. We conclude that cutslopes can be considered the main source of sediments in our study sites, but the function of road surface as a source of runoff generation is more important.

Forest Fringe Communities Participation in Forest Reserve Sustainability in Ghana

The paper investigated the forest fringe community’s participation in forest reserve sustainability in Ghana using Brong-Ahafo Region of Ghana as a case study. The key issues examined are the forest reserve management strategies, stakeholder’s participation and livelihood activities of forest fringe communities. Two stage sampling technique was used to sample forty-two respondents for the study. A structured questionnaire in an interview form was used to solicit information from the respondents. Descriptive statistics was used to analyse the data. The results of the study indicate that there is a management plan for the forest reserve but Forest Services Division (FSD) does not follow its prescriptions strictly, the involvement of Forest Fringe Communities (FFCs) by FSD in the management of the forest reserve was insignificant and evidence of FSD not establishing income generating activity for FFCs livelihood sustenance. It is therefore recommended that community members should be empowered to play the role of co-managers of the forest reserve and there should be regular visit and interaction between FSD and the FFCs.

Pitfalls in forest carbon sink projection

Global forests are increasingly crucial for achiev-ing net-zero carbon emissions,with a quarter of the miti-gation efforts under the Paris Climate Agreement directed towards forests.In China,forests currently contribute to 13%of the global land’s carbon sink,but their stability and per-sistence remain uncertain.We examined and identified that published studies suffered from oversimplifications of eco-system succession and tree demographic dynamics,as well as poor constraints on land quality.Consequently,substan-tial estimations might have been suffered from underrepre-sented or ignored crucial factors,including tree demographic dynamics,and disturbances and habitat shifts caused by global climate change.We argue that these essential factors should be considered to enhance the reliability and accuracy of assessments of the potential for forest carbon sinks.