A multi-function protecting forest system was planed and arranged elaborately for im-provement of the local ecological conditions and high economical benefit. The system in-cludes level farmland shelter belt network, ...A multi-function protecting forest system was planed and arranged elaborately for im-provement of the local ecological conditions and high economical benefit. The system in-cludes level farmland shelter belt network, hillside farmland shelter belt network, stereoscop-ic sparse-wood pasture, erosion control fuel forest, fast growing commercial forest, eco-nomical forest, salt-soda controlling project and salt-soda protecting forest on salt-sodaland, ect..展开更多
Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations...Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.展开更多
Evapotranspiration is an important parameter used to characterize the water cycle of ecosystems.To under-stand the properties of the evapotranspiration and energy balance of a subalpine forest in the southeastern Qing...Evapotranspiration is an important parameter used to characterize the water cycle of ecosystems.To under-stand the properties of the evapotranspiration and energy balance of a subalpine forest in the southeastern Qinghai-Tibet Plateau,an open-path eddy covariance system was set up to monitor the forest from November 2020 to October 2021 in a core area of the Three Parallel Rivers in the Qing-hai-Tibet Plateau.The results show that the evapotranspira-tion peaked daily,the maximum occurring between 11:00 and 15:00.Environmental factors had significant effects on evapotranspiration,among them,net radiation the greatest(R^(2)=0.487),and relative humidity the least(R^(2)=0.001).The energy flux varied considerably in different seasons and sensible heat flux accounted for the main part of turbulent energy.The energy balance ratio in the dormant season was less than that in the growing season,and there is an energy imbalance at the site on an annual time scale.展开更多
As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance le...As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers.On the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule.The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications.The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy.Hence,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF model.In the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,respectively.To examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR.Evaluation of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied models.The newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed RF.Also,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHAP)method,and it was found that thrust force per cutter is the most important variable on TBMAR.The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.展开更多
Background:Nitrogen(N)deposition affects forest stoichiometric flexibility through changing soil nutrient availability to influence plant uptake.However,the effect of N deposition on the flexibility of carbon(C),N,and...Background:Nitrogen(N)deposition affects forest stoichiometric flexibility through changing soil nutrient availability to influence plant uptake.However,the effect of N deposition on the flexibility of carbon(C),N,and phosphorus(P)in forest plant-soil-microbe systems remains unclear.Methods:We conducted a meta-analysis based on 751 pairs of observations to evaluate the responses of plant,soil and microbial biomass C,N and P nutrients and stoichiometry to N addition in different N intensity(050,50–100,>100 kg·ha^(-1)·year^(-1)of N),duration(0–5,>5 year),method(understory,canopy),and matter(ammonium N,nitrate N,organic N,mixed N).Results:N addition significantly increased plant N:P(leaf:14.98%,root:13.29%),plant C:P(leaf:6.8%,root:25.44%),soil N:P(13.94%),soil C:P(10.86%),microbial biomass N:P(23.58%),microbial biomass C:P(12.62%),but reduced plant C:N(leaf:6.49%,root:9.02%).Furthermore,plant C:N:P stoichiometry changed significantly under short-term N inputs,while soil and microorganisms changed drastically under high N addition.Canopy N addition primarily affected plant C:N:P stoichiometry through altering plant N content,while understory N inputs altered more by influencing soil C and P content.Organic N significantly influenced plant and soil C:N and C:P,while ammonia N changed plant N:P.Plant C:P and soil C:N were strongly correlated with mean annual precipitation(MAT),and the C:N:P stoichiometric flexibility in soil and plant under N addition connected with soil depth.Besides,N addition decoupled the correlations between soil microorganisms and the plant.Conclusions:N addition significantly increased the C:P and N:P in soil,plant,and microbial biomass,reducing plant C:N,and aggravated forest P limitations.Significantly,these impacts were contingent on climate types,soil layers,and N input forms.The findings enhance our comprehension of the plant-soil system nutrient cycling mechanisms in forest ecosystems and plant strategy responses to N deposition.展开更多
Thinning is a widely used forest management tool but systematic research has not been carried out to verify its eff ects on carbon storage and plant diversity at the ecosystem level.In this study,the eff ect of thinni...Thinning is a widely used forest management tool but systematic research has not been carried out to verify its eff ects on carbon storage and plant diversity at the ecosystem level.In this study,the eff ect of thinning was assessed across seven thinning intensities(0,10,15,20,25,30 and 35%)in a low-quality secondary forest in NE China over a ten-year period.Thinning aff ected the carbon storage of trees,and shrub,herb,and soil layers(P<0.05).It fi rst increased and then decreased as thinning intensity increased,reaching its maximum at 30%thinning.Carbon storage of the soil accounted for more than 64%of the total carbon stored in the ecosystem.It was highest in the upper 20-cm soil layer.Thinning increased tree species diversity while decreasing shrub and herb diversities(P<0.05).Redundancy analysis and a correlation heat map showed that carbon storage of tree and shrub layers was positively correlated with tree diversity but negatively with herb diversity,indicating that the increase in tree diversity increased the carbon storage of natural forest ecosystems.Although thinning decreased shrub and herb diversities,it increased the carbon storage of the overall ecosystem and tree species diversity of secondary forest.Maximum carbon storage and the highest tree diversity were observed at a thinning intensity of 30%.This study provides evidence for the ecological management of natural and secondary forests and improvement of ecosystem carbon sinks and biodiversity.展开更多
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 managem...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.展开更多
A huge number of old arch bridges located in rural regions are at the peak of maintenance.The health monitoring technology of the long-span bridge is hardly applicable to the small-span bridge,owing to the absence of ...A huge number of old arch bridges located in rural regions are at the peak of maintenance.The health monitoring technology of the long-span bridge is hardly applicable to the small-span bridge,owing to the absence of technical resources and sufficient funds in rural regions.There is an urgent need for an economical,fast,and accurate damage identification solution.The authors proposed a damage identification system of an old arch bridge implemented with amachine learning algorithm,which took the vehicle-induced response as the excitation.A damage index was defined based on wavelet packet theory,and a machine learning sample database collecting the denoised response was constructed.Through comparing three machine learning algorithms:Back-Propagation Neural Network(BPNN),Support Vector Machine(SVM),and Random Forest(R.F.),the R.F.damage identification model were found to have a better recognition ability.Finally,the Particle Swarm Optimization(PSO)algorithm was used to optimize the number of subtrees and split features of the R.F.model.The PSO optimized R.F.model was capable of the identification of different damage levels of old arch bridges with sensitive damage index.The proposed framework is practical and promising for the old bridge’s structural damage identification in rural regions.展开更多
Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau.Climate-growth relationship analysis indicated that the two co-e...Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau.Climate-growth relationship analysis indicated that the two co-exist-ing species reponded similarly to climate factors,although S.saltuaria was more sensitive than A.faxoniana.The strong-est correlation was between S.saltuaria chronology and regional mean temperatures from June to November.Based on this relationship,a regional mean temperature from June to November for the period 1605-2016 was constructed.Reconstruction explained 37.3%of the temperature variance during th period 1961-2016.Six major warm periods and five major cold periods were identified.Spectral analysis detected significant interannual and multi-decadal cycles.Reconstruction also revealed the influence of the Atlantic Multi-decadal Oscillation,confirming its importance on climate change on the eastern Tibetan Plateau.展开更多
Ecosystem services(ES)are the connection between nature and society,and are essential for the well-being of local communities that depend on them.In Ethiopia,church forests and the surrounding agricultural matrix supp...Ecosystem services(ES)are the connection between nature and society,and are essential for the well-being of local communities that depend on them.In Ethiopia,church forests and the surrounding agricultural matrix supply numerous ES.However,the ES delivered by both land use types have not yet been assessed simultaneously.Here we surveyed both church forests and their agricultural matrices,aiming to quantify,compare and unravel the drivers underlying tree-based ES supply,density and multifunctionality.We found that almost all church forests and half of the agricultural matrices provided high ES densities.ES multifunctionality was higher in the agricultural matrices,suggesting that people deliberately conserve or plant multifunctional tree species.Furthermore,the supply of all categories of ES was positively correlated with church forest age(p-value<0.001)in the agricultural matrix,while the extent of church forest was positively correlated with the density of all categories ecosystem services score in the church forests(p-value<0.001).Our results can be used to prioritize conservation efforts at sites that provide high levels of ES supply,ES density and ES multifunctionality,and to prioritize restoration efforts at sites with low levels thereof.展开更多
Invasive plant Ageratina adenophora(Sprengel)R.King&H.Robinson has invaded majority of the temperate forests in Kumaun,Central Himalaya.Information on A.adenophora invaded forest types,their structural attributes,...Invasive plant Ageratina adenophora(Sprengel)R.King&H.Robinson has invaded majority of the temperate forests in Kumaun,Central Himalaya.Information on A.adenophora invaded forest types,their structural attributes,population demography and regeneration status are still at rudimentary level.Considering this,the present study was conducted to assess the impacts of A.adenophora on vegetational attributes and regeneration status of three forest types,viz.,Oak(Quercus oblongata D.Don),Pine(Pinus roxburghii Sarg.)and Cypress(Cupressus torulosa D.Don).We selected three sites for each forest type and each site was further purposively stratified into paired sampling plots of 1 ha each i.e.,A.adenophora invaded and uninvaded sites.Our results showed large densities of cut stumps or felled trees throughout invaded sites,but with fewer fire signs in comparison to uninvaded sites.In uninvaded sites,total density and basal area calculated for woody species were relatively higher than those in invaded sites,although results were insignificant(p>0.05).With the exception for Cypress forests,vegetation indices showed low woody species richness and diversity in invaded Oak and Pine forests.Also,regeneration of Q.oblongata,P.roxburghii and C.torulosa tree species did not differ significantly(p>0.05)between invaded and uninvaded sites.These insignificant differences clearly imply that A.adenophora's presence has not entirely changed the perennial plant communities in terms of composition,structure and natural regeneration.However,tree species with poor or no regeneration status requires special attention and needs management strategies involving control of invasive species in forest ecosystems.展开更多
The aim of the work was to determine the spatial distribution of activity in the forest on the area of the Forest Promotional Complex“Sudety Zachodnie”using mobile phone data.The study identified the sites with the ...The aim of the work was to determine the spatial distribution of activity in the forest on the area of the Forest Promotional Complex“Sudety Zachodnie”using mobile phone data.The study identified the sites with the highest(hot spot)and lowest(cold spot)use.Habitat,stand,demographic,topographic and spatial factors affecting the distribution of activity were also analyzed.Two approaches were applied in our research:global and local Moran’s coefficients,and a machine learning technique,Boosted Regression Trees.The results show that 11,503,320 visits to forest areas were recorded in the“Sudety Zachodnie”in 2019.The most popular season for activities was winter,and the least popular was spring.Using global and local Moran’s I coefficients,three small hot clusters of activity and one large cold cluster were identified.Locations with high values with similar neighbours(hot-spots)were most often visited forest areas,averaging almost 200,000 visits over 2019.Significantly fewer visits were recorded in cold-spots,the average number of visits to these areas was about 4,500.The value of global Moran’s I was equal to 0.54 and proved significant positive spatial autocorrelation.Results of Boosted Regression Trees modeling of visits in forest,using tree stand habitat and spatial factors accurately explained 76%of randomly selected input data.The variables that had the greatest effect on the distribution of activities were the density of hiking and biking trails and diversity of topography.The methodology presented in this article allows delineation of Cultural Ecosystem Services hot spots in forest areas based on mobile phone data.It also allows the identification of factors that may influence the distribution of visits in forests.Such data are important for managing forest areas and adapting forest management to the needs of society while maintaining ecosystem stability.展开更多
Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire char...Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire characteristics,regional assessment of fire severity is crucial.The objectives of this study were:(1)to test the performance of different satellite imagery and spectral indices,and two field—measured severity indices,CBI(Composite Burn Index)and GeoCBI(Geometrically structured Composite Burn Index)to assess fire severity;(2)to calculate classification thresholds for spectral indices that performed best in the study areas;and(3)to generate fire severity maps that could be used to determine the ecological impact of forest fires.Five large fires in Pinus brutia(Turkish pine)and Pinus nigra subsp.pallasiana var.pallasiana(Anatolian black pine)—dominated forests during 2020 and 2021 were selected as study sites.The results show that GeoCBI provided more reliable estimates of field—measured fire severity than CBI.While Sentinel-2 and Landsat-8/OLI images performed similarly well,MODIS performed poorly.Fire severity classification thresholds were determined for Sentinel-2 based RdNBR,dNBR,dSAVI,dNDVI,and dNDMI and Landsat-8/OLI based dNBR,dNDVI,and dSAVI.Among several spectral indices,the highest accuracy for fire severity classification was found for Sentinel-2 based RdNBR(72.1%)and Landsat-8/OLI based dNBR(69.2%).The results can be used to assess and map fire severity in forest ecosystems similar to those in this study.展开更多
Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance o...Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.展开更多
Objective Body fluid mixtures are complex biological samples that frequently occur in crime scenes,and can provide important clues for criminal case analysis.DNA methylation assay has been applied in the identificatio...Objective Body fluid mixtures are complex biological samples that frequently occur in crime scenes,and can provide important clues for criminal case analysis.DNA methylation assay has been applied in the identification of human body fluids,and has exhibited excellent performance in predicting single-source body fluids.The present study aims to develop a methylation SNaPshot multiplex system for body fluid identification,and accurately predict the mixture samples.In addition,the value of DNA methylation in the prediction of body fluid mixtures was further explored.Methods In the present study,420 samples of body fluid mixtures and 250 samples of single body fluids were tested using an optimized multiplex methylation system.Each kind of body fluid sample presented the specific methylation profiles of the 10 markers.Results Significant differences in methylation levels were observed between the mixtures and single body fluids.For all kinds of mixtures,the Spearman’s correlation analysis revealed a significantly strong correlation between the methylation levels and component proportions(1:20,1:10,1:5,1:1,5:1,10:1 and 20:1).Two random forest classification models were trained for the prediction of mixture types and the prediction of the mixture proportion of 2 components,based on the methylation levels of 10 markers.For the mixture prediction,Model-1 presented outstanding prediction accuracy,which reached up to 99.3%in 427 training samples,and had a remarkable accuracy of 100%in 243 independent test samples.For the mixture proportion prediction,Model-2 demonstrated an excellent accuracy of 98.8%in 252 training samples,and 98.2%in 168 independent test samples.The total prediction accuracy reached 99.3%for body fluid mixtures and 98.6%for the mixture proportions.Conclusion These results indicate the excellent capability and powerful value of the multiplex methylation system in the identification of forensic body fluid mixtures.展开更多
The latest advancements in computer vision and deep learning(DL)techniques pave the way to design novel tools for the detection and monitoring of forestfires.In this view,this paper presents an intelligent wild forestfi...The latest advancements in computer vision and deep learning(DL)techniques pave the way to design novel tools for the detection and monitoring of forestfires.In this view,this paper presents an intelligent wild forestfire detec-tion and alarming system using deep learning(IWFFDA-DL)model.The pro-posed IWFFDA-DL technique aims to identify forestfires at earlier stages through integrated sensors.The proposed IWFFDA-DL system includes an Inte-grated sensor system(ISS)combining an array of sensors that acts as the major input source that helps to forecast thefire.Then,the attention based convolution neural network with bidirectional long short term memory(ACNN-BLSTM)model is applied to examine and identify the existence of danger.For hyperpara-meter tuning of the ACNN-BLSTM model,the bacterial foraging optimization(BFO)algorithm is employed and thereby enhances the detection performance.Finally,when thefire is detected,the Global System for Mobiles(GSM)modem transmits messages to the authorities to take required actions.An extensive set of simulations were performed and the results are investigated interms of several aspects.The obtained results highlight the betterment of the IWFFDA-DL techni-que interms of various measures.展开更多
Taking Wutong Mountain Rhododendron moulmainense ecological landscape forest in Shenzhen City as an example,the value of the forest was assessed by constructing an ecological service value assessment system and accoun...Taking Wutong Mountain Rhododendron moulmainense ecological landscape forest in Shenzhen City as an example,the value of the forest was assessed by constructing an ecological service value assessment system and accounting method.The assessment results showed that the total ecosystem service value of R.moulmainense ecological landscape forest was 13.195 billion yuan,and the top three services included the value of forestry products,the value of biodiversity maintenance and the value of leisure and recreation,indicating that the ecosystem service of Wutong Mountain R.moulmainense ecological landscape forest in Shenzhen has great ecological and economic value,especially in forestry products,biodiversity maintenance,and leisure and recreation.展开更多
The disappearance of resources with high genetic potential and great utility for people and the challenge of the conservation and sustainable management of these resources are two opposing facts of which the world is ...The disappearance of resources with high genetic potential and great utility for people and the challenge of the conservation and sustainable management of these resources are two opposing facts of which the world is now concerned. In Benin, forests and agroforestry systems complement each other in wood supply for mortar and pestle manufacture. Thus, this study aimed to investigate the diversity of woody species used for mortar and pestle manufacture and to analyze the preferences of manufacturers through an ethnobotanical approach. Based on the snowball sampling method, and interviews with 112 manufacturers from different ethnic groups, we identified 31 tree species. These species belong to 30 genera and 13 plant families. The Fabaceae are more represented with 14 species (i.e. 45% of the total). Ten are frequently used. But there are four species, such as Vitellaria paradoxa C. F. Gaertn., Prosopis africana (Guill. & Perr.) Taub., Terminalia glaucescens Planch. ex Benth. and Pericopsis laxiflora (Benth.) Meeuwen, which are highly preferred by manufacturers respectively. The calculation of the Indexes of Possession of Global Knowledge (IPSG) revealed that the ethnic group Nagot (0.204) possessed more knowledge and is followed by Mahi (0.201) and Fon (0.18) respectively. Forests and agroforestry systems are both supply sites for manufacturers. The non-parametric Wilcoxon test proved that there are no significant differences between the species’ preference for mortars or pestles manufacture (v = 181, p-value = 0.38). Since the trees cutting in agroforestry systems can be destructive to them, provisions such as the promotion of agroforestry in rural areas and the integration of the used species in the reforestations programs must be taken to curb the pressure and contribute to the conservation of the biodiversity.展开更多
Forest plays a crucial role in providing essential ecosystem services, including water supply, climate regulation, and biodiversity conservation. This study aimed to assess the current state of the forest in Barangay ...Forest plays a crucial role in providing essential ecosystem services, including water supply, climate regulation, and biodiversity conservation. This study aimed to assess the current state of the forest in Barangay Nambalan, Mayantoc, Tarlac. The specific objectives were to identify tree species in the area and determine the tree diversity index, with a focus on endemism and conservation status. Two transect lines, each spanning one kilometer, were established and a total of 10 sampling quadrats were surveyed. Ecological parameters (relative frequency, relative density, relative dominance, and importance value index) and diversity indices (Shannon-Weiner index, Simpson’s index) were computed using the Paleontological Statistic Software Package for Educational Analysis (PAST 4.03). A comprehensive inventory revealed a total of 756 individuals representing 52 species, 46 genera, and 25 families. Among the recorded species, 10 (17.2%) were endemic and 11 (21.6%) were classified as threatened. The Fabaceae (20.8%), Moraceae (14.6%), and Euphorbiaceae (8.3%) were identified as the most abundant families. The computed diversity indices indicated that Barangay Nambalan retains a diverse forest cover;however, species composition was found to be relatively low. Based on the finding, this study recommends the strict enforcement of protective measures and legislation to mitigate further degradation of the remaining forest in Barangay Nambalan.展开更多
文摘A multi-function protecting forest system was planed and arranged elaborately for im-provement of the local ecological conditions and high economical benefit. The system in-cludes level farmland shelter belt network, hillside farmland shelter belt network, stereoscop-ic sparse-wood pasture, erosion control fuel forest, fast growing commercial forest, eco-nomical forest, salt-soda controlling project and salt-soda protecting forest on salt-sodaland, ect..
基金This research was funded by the National Natural Science Foundation of China(Grant Nos.31870426).
文摘Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.
基金supported by the CAS"Light of West China"Program (2021XBZG-XBQNXZ-A-007)the National Natural Science Foundation of China (31971436)the State Key Laboratory of Cryospheric Science,Northwest Institute of Eco-Environment and Resources,Chinese Academy Sciences (SKLCS-OP-2021-06).
文摘Evapotranspiration is an important parameter used to characterize the water cycle of ecosystems.To under-stand the properties of the evapotranspiration and energy balance of a subalpine forest in the southeastern Qinghai-Tibet Plateau,an open-path eddy covariance system was set up to monitor the forest from November 2020 to October 2021 in a core area of the Three Parallel Rivers in the Qing-hai-Tibet Plateau.The results show that the evapotranspira-tion peaked daily,the maximum occurring between 11:00 and 15:00.Environmental factors had significant effects on evapotranspiration,among them,net radiation the greatest(R^(2)=0.487),and relative humidity the least(R^(2)=0.001).The energy flux varied considerably in different seasons and sensible heat flux accounted for the main part of turbulent energy.The energy balance ratio in the dormant season was less than that in the growing season,and there is an energy imbalance at the site on an annual time scale.
基金the National Natural Science Foundation of China(Grant 42177164)the Distinguished Youth Science Foundation of Hunan Province of China(2022JJ10073).
文摘As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers.On the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule.The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications.The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy.Hence,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF model.In the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,respectively.To examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR.Evaluation of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied models.The newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed RF.Also,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHAP)method,and it was found that thrust force per cutter is the most important variable on TBMAR.The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.
基金supported by the National Natural Science Foundation of China(Nos.31800369,32271686,U1904204)the State Scholarship Fund of Chinathe Innovation Scientists and Technicians Troop Construction Projects of Henan Province(No.182101510005)。
文摘Background:Nitrogen(N)deposition affects forest stoichiometric flexibility through changing soil nutrient availability to influence plant uptake.However,the effect of N deposition on the flexibility of carbon(C),N,and phosphorus(P)in forest plant-soil-microbe systems remains unclear.Methods:We conducted a meta-analysis based on 751 pairs of observations to evaluate the responses of plant,soil and microbial biomass C,N and P nutrients and stoichiometry to N addition in different N intensity(050,50–100,>100 kg·ha^(-1)·year^(-1)of N),duration(0–5,>5 year),method(understory,canopy),and matter(ammonium N,nitrate N,organic N,mixed N).Results:N addition significantly increased plant N:P(leaf:14.98%,root:13.29%),plant C:P(leaf:6.8%,root:25.44%),soil N:P(13.94%),soil C:P(10.86%),microbial biomass N:P(23.58%),microbial biomass C:P(12.62%),but reduced plant C:N(leaf:6.49%,root:9.02%).Furthermore,plant C:N:P stoichiometry changed significantly under short-term N inputs,while soil and microorganisms changed drastically under high N addition.Canopy N addition primarily affected plant C:N:P stoichiometry through altering plant N content,while understory N inputs altered more by influencing soil C and P content.Organic N significantly influenced plant and soil C:N and C:P,while ammonia N changed plant N:P.Plant C:P and soil C:N were strongly correlated with mean annual precipitation(MAT),and the C:N:P stoichiometric flexibility in soil and plant under N addition connected with soil depth.Besides,N addition decoupled the correlations between soil microorganisms and the plant.Conclusions:N addition significantly increased the C:P and N:P in soil,plant,and microbial biomass,reducing plant C:N,and aggravated forest P limitations.Significantly,these impacts were contingent on climate types,soil layers,and N input forms.The findings enhance our comprehension of the plant-soil system nutrient cycling mechanisms in forest ecosystems and plant strategy responses to N deposition.
基金supported by the Applied Technology Research and Development program of Heilongjiang Province(GA19C006)the Innovation Foundation for Doctoral Program of Forestry Engineering of Northeast Forestry University(LYGC202112).
文摘Thinning is a widely used forest management tool but systematic research has not been carried out to verify its eff ects on carbon storage and plant diversity at the ecosystem level.In this study,the eff ect of thinning was assessed across seven thinning intensities(0,10,15,20,25,30 and 35%)in a low-quality secondary forest in NE China over a ten-year period.Thinning aff ected the carbon storage of trees,and shrub,herb,and soil layers(P<0.05).It fi rst increased and then decreased as thinning intensity increased,reaching its maximum at 30%thinning.Carbon storage of the soil accounted for more than 64%of the total carbon stored in the ecosystem.It was highest in the upper 20-cm soil layer.Thinning increased tree species diversity while decreasing shrub and herb diversities(P<0.05).Redundancy analysis and a correlation heat map showed that carbon storage of tree and shrub layers was positively correlated with tree diversity but negatively with herb diversity,indicating that the increase in tree diversity increased the carbon storage of natural forest ecosystems.Although thinning decreased shrub and herb diversities,it increased the carbon storage of the overall ecosystem and tree species diversity of secondary forest.Maximum carbon storage and the highest tree diversity were observed at a thinning intensity of 30%.This study provides evidence for the ecological management of natural and secondary forests and improvement of ecosystem carbon sinks and biodiversity.
基金the Catalan Government Predoctoral Schol-arship(AGAUR-FSE 2020 FI_B200147)SuFoRun Marie Sklodowska-Curie Research and Innovation Staff Exchange(RISE)Program(Grant No.691149)the Spanish Ministry of Science and Innovation(PID2020-120355RB-IOO).
文摘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.
基金supported by the Elite Scholar Program of Northwest A&F University (Grant No.Z111022001)the Research Fund of Department of Transport of Shannxi Province (Grant No.22-23K)the Student Innovation and Entrepreneurship Training Program of China (Project Nos.S202110712555 and S202110712534).
文摘A huge number of old arch bridges located in rural regions are at the peak of maintenance.The health monitoring technology of the long-span bridge is hardly applicable to the small-span bridge,owing to the absence of technical resources and sufficient funds in rural regions.There is an urgent need for an economical,fast,and accurate damage identification solution.The authors proposed a damage identification system of an old arch bridge implemented with amachine learning algorithm,which took the vehicle-induced response as the excitation.A damage index was defined based on wavelet packet theory,and a machine learning sample database collecting the denoised response was constructed.Through comparing three machine learning algorithms:Back-Propagation Neural Network(BPNN),Support Vector Machine(SVM),and Random Forest(R.F.),the R.F.damage identification model were found to have a better recognition ability.Finally,the Particle Swarm Optimization(PSO)algorithm was used to optimize the number of subtrees and split features of the R.F.model.The PSO optimized R.F.model was capable of the identification of different damage levels of old arch bridges with sensitive damage index.The proposed framework is practical and promising for the old bridge’s structural damage identification in rural regions.
基金This study was supported by the National Key Research and Development Program of China(No.2018YFA0605601)Hong Kong Research Grants Council(No.106220169)+1 种基金the National Natural Science Foundation of China(Nos.41671042,42077417,42105155,and 42201083)the National Geographic Society(No.EC-95776R-22).
文摘Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau.Climate-growth relationship analysis indicated that the two co-exist-ing species reponded similarly to climate factors,although S.saltuaria was more sensitive than A.faxoniana.The strong-est correlation was between S.saltuaria chronology and regional mean temperatures from June to November.Based on this relationship,a regional mean temperature from June to November for the period 1605-2016 was constructed.Reconstruction explained 37.3%of the temperature variance during th period 1961-2016.Six major warm periods and five major cold periods were identified.Spectral analysis detected significant interannual and multi-decadal cycles.Reconstruction also revealed the influence of the Atlantic Multi-decadal Oscillation,confirming its importance on climate change on the eastern Tibetan Plateau.
基金flnancial support from VLIR-UOS,Belgium through the VLIR-IUC Interuniversity cooperation with Bahir Dar University,Ethiopia (BDU-IUC)
文摘Ecosystem services(ES)are the connection between nature and society,and are essential for the well-being of local communities that depend on them.In Ethiopia,church forests and the surrounding agricultural matrix supply numerous ES.However,the ES delivered by both land use types have not yet been assessed simultaneously.Here we surveyed both church forests and their agricultural matrices,aiming to quantify,compare and unravel the drivers underlying tree-based ES supply,density and multifunctionality.We found that almost all church forests and half of the agricultural matrices provided high ES densities.ES multifunctionality was higher in the agricultural matrices,suggesting that people deliberately conserve or plant multifunctional tree species.Furthermore,the supply of all categories of ES was positively correlated with church forest age(p-value<0.001)in the agricultural matrix,while the extent of church forest was positively correlated with the density of all categories ecosystem services score in the church forests(p-value<0.001).Our results can be used to prioritize conservation efforts at sites that provide high levels of ES supply,ES density and ES multifunctionality,and to prioritize restoration efforts at sites with low levels thereof.
基金Department of Science&Technology,New Delhi(DST-SERB/CRG/2019/004139)for providing financial support。
文摘Invasive plant Ageratina adenophora(Sprengel)R.King&H.Robinson has invaded majority of the temperate forests in Kumaun,Central Himalaya.Information on A.adenophora invaded forest types,their structural attributes,population demography and regeneration status are still at rudimentary level.Considering this,the present study was conducted to assess the impacts of A.adenophora on vegetational attributes and regeneration status of three forest types,viz.,Oak(Quercus oblongata D.Don),Pine(Pinus roxburghii Sarg.)and Cypress(Cupressus torulosa D.Don).We selected three sites for each forest type and each site was further purposively stratified into paired sampling plots of 1 ha each i.e.,A.adenophora invaded and uninvaded sites.Our results showed large densities of cut stumps or felled trees throughout invaded sites,but with fewer fire signs in comparison to uninvaded sites.In uninvaded sites,total density and basal area calculated for woody species were relatively higher than those in invaded sites,although results were insignificant(p>0.05).With the exception for Cypress forests,vegetation indices showed low woody species richness and diversity in invaded Oak and Pine forests.Also,regeneration of Q.oblongata,P.roxburghii and C.torulosa tree species did not differ significantly(p>0.05)between invaded and uninvaded sites.These insignificant differences clearly imply that A.adenophora's presence has not entirely changed the perennial plant communities in terms of composition,structure and natural regeneration.However,tree species with poor or no regeneration status requires special attention and needs management strategies involving control of invasive species in forest ecosystems.
基金Funded by the National Science Centre,Poland under the OPUS call in the Weave programme(project No.2021/43/I/HS4/01451)funded by Ministry of Education and Science(901503)。
文摘The aim of the work was to determine the spatial distribution of activity in the forest on the area of the Forest Promotional Complex“Sudety Zachodnie”using mobile phone data.The study identified the sites with the highest(hot spot)and lowest(cold spot)use.Habitat,stand,demographic,topographic and spatial factors affecting the distribution of activity were also analyzed.Two approaches were applied in our research:global and local Moran’s coefficients,and a machine learning technique,Boosted Regression Trees.The results show that 11,503,320 visits to forest areas were recorded in the“Sudety Zachodnie”in 2019.The most popular season for activities was winter,and the least popular was spring.Using global and local Moran’s I coefficients,three small hot clusters of activity and one large cold cluster were identified.Locations with high values with similar neighbours(hot-spots)were most often visited forest areas,averaging almost 200,000 visits over 2019.Significantly fewer visits were recorded in cold-spots,the average number of visits to these areas was about 4,500.The value of global Moran’s I was equal to 0.54 and proved significant positive spatial autocorrelation.Results of Boosted Regression Trees modeling of visits in forest,using tree stand habitat and spatial factors accurately explained 76%of randomly selected input data.The variables that had the greatest effect on the distribution of activities were the density of hiking and biking trails and diversity of topography.The methodology presented in this article allows delineation of Cultural Ecosystem Services hot spots in forest areas based on mobile phone data.It also allows the identification of factors that may influence the distribution of visits in forests.Such data are important for managing forest areas and adapting forest management to the needs of society while maintaining ecosystem stability.
基金funded by the Turkish General Directorate of Forestry(project number:19.9402/2020-2023)。
文摘Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire characteristics,regional assessment of fire severity is crucial.The objectives of this study were:(1)to test the performance of different satellite imagery and spectral indices,and two field—measured severity indices,CBI(Composite Burn Index)and GeoCBI(Geometrically structured Composite Burn Index)to assess fire severity;(2)to calculate classification thresholds for spectral indices that performed best in the study areas;and(3)to generate fire severity maps that could be used to determine the ecological impact of forest fires.Five large fires in Pinus brutia(Turkish pine)and Pinus nigra subsp.pallasiana var.pallasiana(Anatolian black pine)—dominated forests during 2020 and 2021 were selected as study sites.The results show that GeoCBI provided more reliable estimates of field—measured fire severity than CBI.While Sentinel-2 and Landsat-8/OLI images performed similarly well,MODIS performed poorly.Fire severity classification thresholds were determined for Sentinel-2 based RdNBR,dNBR,dSAVI,dNDVI,and dNDMI and Landsat-8/OLI based dNBR,dNDVI,and dSAVI.Among several spectral indices,the highest accuracy for fire severity classification was found for Sentinel-2 based RdNBR(72.1%)and Landsat-8/OLI based dNBR(69.2%).The results can be used to assess and map fire severity in forest ecosystems similar to those in this study.
基金funded by the National Key R&D Program of China(Grant No.2021YFD1500200)National Natural Science Foundation of China(Grant No.42077149)+4 种基金China Postdoctoral Science Foundation(Grant No.2019M660782)National Science and Technology Basic Resources Survey Program of China(Grant No.2019FY101300)Doctoral research start-up fund project of Liaoning Provincial Department of Science and Technology(Grant No.2021-BS-136)China Scholarship Council(201908210132)Young Scientific and Technological Talents Project of Liaoning Province(Grant Nos.LSNQN201910 and LSNQN201914)。
文摘Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.
基金supported by the grants from the Natural Science Foundation of Hubei Province(No.2020CFB780)the Fundamental Research Funds for the Central Universities(No.2017KFYXJJ020).
文摘Objective Body fluid mixtures are complex biological samples that frequently occur in crime scenes,and can provide important clues for criminal case analysis.DNA methylation assay has been applied in the identification of human body fluids,and has exhibited excellent performance in predicting single-source body fluids.The present study aims to develop a methylation SNaPshot multiplex system for body fluid identification,and accurately predict the mixture samples.In addition,the value of DNA methylation in the prediction of body fluid mixtures was further explored.Methods In the present study,420 samples of body fluid mixtures and 250 samples of single body fluids were tested using an optimized multiplex methylation system.Each kind of body fluid sample presented the specific methylation profiles of the 10 markers.Results Significant differences in methylation levels were observed between the mixtures and single body fluids.For all kinds of mixtures,the Spearman’s correlation analysis revealed a significantly strong correlation between the methylation levels and component proportions(1:20,1:10,1:5,1:1,5:1,10:1 and 20:1).Two random forest classification models were trained for the prediction of mixture types and the prediction of the mixture proportion of 2 components,based on the methylation levels of 10 markers.For the mixture prediction,Model-1 presented outstanding prediction accuracy,which reached up to 99.3%in 427 training samples,and had a remarkable accuracy of 100%in 243 independent test samples.For the mixture proportion prediction,Model-2 demonstrated an excellent accuracy of 98.8%in 252 training samples,and 98.2%in 168 independent test samples.The total prediction accuracy reached 99.3%for body fluid mixtures and 98.6%for the mixture proportions.Conclusion These results indicate the excellent capability and powerful value of the multiplex methylation system in the identification of forensic body fluid mixtures.
文摘The latest advancements in computer vision and deep learning(DL)techniques pave the way to design novel tools for the detection and monitoring of forestfires.In this view,this paper presents an intelligent wild forestfire detec-tion and alarming system using deep learning(IWFFDA-DL)model.The pro-posed IWFFDA-DL technique aims to identify forestfires at earlier stages through integrated sensors.The proposed IWFFDA-DL system includes an Inte-grated sensor system(ISS)combining an array of sensors that acts as the major input source that helps to forecast thefire.Then,the attention based convolution neural network with bidirectional long short term memory(ACNN-BLSTM)model is applied to examine and identify the existence of danger.For hyperpara-meter tuning of the ACNN-BLSTM model,the bacterial foraging optimization(BFO)algorithm is employed and thereby enhances the detection performance.Finally,when thefire is detected,the Global System for Mobiles(GSM)modem transmits messages to the authorities to take required actions.An extensive set of simulations were performed and the results are investigated interms of several aspects.The obtained results highlight the betterment of the IWFFDA-DL techni-que interms of various measures.
文摘Taking Wutong Mountain Rhododendron moulmainense ecological landscape forest in Shenzhen City as an example,the value of the forest was assessed by constructing an ecological service value assessment system and accounting method.The assessment results showed that the total ecosystem service value of R.moulmainense ecological landscape forest was 13.195 billion yuan,and the top three services included the value of forestry products,the value of biodiversity maintenance and the value of leisure and recreation,indicating that the ecosystem service of Wutong Mountain R.moulmainense ecological landscape forest in Shenzhen has great ecological and economic value,especially in forestry products,biodiversity maintenance,and leisure and recreation.
文摘The disappearance of resources with high genetic potential and great utility for people and the challenge of the conservation and sustainable management of these resources are two opposing facts of which the world is now concerned. In Benin, forests and agroforestry systems complement each other in wood supply for mortar and pestle manufacture. Thus, this study aimed to investigate the diversity of woody species used for mortar and pestle manufacture and to analyze the preferences of manufacturers through an ethnobotanical approach. Based on the snowball sampling method, and interviews with 112 manufacturers from different ethnic groups, we identified 31 tree species. These species belong to 30 genera and 13 plant families. The Fabaceae are more represented with 14 species (i.e. 45% of the total). Ten are frequently used. But there are four species, such as Vitellaria paradoxa C. F. Gaertn., Prosopis africana (Guill. & Perr.) Taub., Terminalia glaucescens Planch. ex Benth. and Pericopsis laxiflora (Benth.) Meeuwen, which are highly preferred by manufacturers respectively. The calculation of the Indexes of Possession of Global Knowledge (IPSG) revealed that the ethnic group Nagot (0.204) possessed more knowledge and is followed by Mahi (0.201) and Fon (0.18) respectively. Forests and agroforestry systems are both supply sites for manufacturers. The non-parametric Wilcoxon test proved that there are no significant differences between the species’ preference for mortars or pestles manufacture (v = 181, p-value = 0.38). Since the trees cutting in agroforestry systems can be destructive to them, provisions such as the promotion of agroforestry in rural areas and the integration of the used species in the reforestations programs must be taken to curb the pressure and contribute to the conservation of the biodiversity.
文摘Forest plays a crucial role in providing essential ecosystem services, including water supply, climate regulation, and biodiversity conservation. This study aimed to assess the current state of the forest in Barangay Nambalan, Mayantoc, Tarlac. The specific objectives were to identify tree species in the area and determine the tree diversity index, with a focus on endemism and conservation status. Two transect lines, each spanning one kilometer, were established and a total of 10 sampling quadrats were surveyed. Ecological parameters (relative frequency, relative density, relative dominance, and importance value index) and diversity indices (Shannon-Weiner index, Simpson’s index) were computed using the Paleontological Statistic Software Package for Educational Analysis (PAST 4.03). A comprehensive inventory revealed a total of 756 individuals representing 52 species, 46 genera, and 25 families. Among the recorded species, 10 (17.2%) were endemic and 11 (21.6%) were classified as threatened. The Fabaceae (20.8%), Moraceae (14.6%), and Euphorbiaceae (8.3%) were identified as the most abundant families. The computed diversity indices indicated that Barangay Nambalan retains a diverse forest cover;however, species composition was found to be relatively low. Based on the finding, this study recommends the strict enforcement of protective measures and legislation to mitigate further degradation of the remaining forest in Barangay Nambalan.