Local perceptions of the conversion of cropland to forestland program in Jiangxi, Shaanxi, and Sichuan, China

Numerous land-use policies have been implemented in China in recent decades for ecological restoration and conservation to reduce environmental disasters and promote environmental sustainability.Many of these policies follow a top-down approach to implementation and as such,emphasize the hierarchical control within government structures.An understanding of local perceptions of land-use policies is important if the disconnect between policy makers and the target population is to be reduced and if program support is to improve.This study aimed to help improve local implementation,attitude toward,and engagement by examining the influence of socio-economic characteristics on the target population’s(local farmers)perception of the conversion of cropland to forestland program(CFPP)land use policy in Jiangxi,Sichuan,and Shaanxi provinces.It uses logistical regression models,with robust aspects of perception including confidence,support,transparency,prospects,fairness,and willingness to participate.Results indicate that social aspects as well as economic aspects are most important in influencing farmers’perceptions towards the CFPP.The farmers who have received technical support,rural male habitants,educated,and non-middle-aged farmers exhibit more positive perceptions of the program and are much more likely to support it,whereas farmers without any technical support or formal education,and female and middle-aged farmers are less likely to support the program.Importantly,this study also reveals the differences in responses,experiences and perceptions of the farmers living across different provinces.These empirical results provide insight into the influence of socio-economic characteristics on the perception of farmers towards land-use policies,which has important implications for designing targeted policy instruments and increasing farmer support for these policies.This knowledge can be harnessed and further evaluated in future research to improve citizen engagement,support,and understanding in order to help ecological restoration and conservation objectives be more effectively achieved.

Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm

Feature selection has been widely used in data mining and machine learning.Its objective is to select a minimal subset of features according to some reasonable criteria so as to solve the original task more quickly.In this article,a feature selection algorithm with local search strategy based on the forest optimization algorithm,namely FSLSFOA,is proposed.The novel local search strategy in local seeding process guarantees the quality of the feature subset in the forest.Next,the fitness function is improved,which not only considers the classification accuracy,but also considers the size of the feature subset.To avoid falling into local optimum,a novel global seeding method is attempted,which selects trees on the bottom of candidate set and gives the algorithm more diversities.Finally,FSLSFOA is compared with four feature selection methods to verify its effectiveness.Most of the results are superior to these comparative methods.

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.

The Role and Effectiveness of Local Institutions in the Management of Forest Biodiversity in New Dabaga-Ulongambi Forest Reserve,Iringa Region-Tanzania

This paper examines the role and effectiveness of locacal institutions in the management of forest biodiversity in New Dabaga-Ulongambi Forest Reserve, Tanzania. Data were obtained through questionnaires, interviews, focus group discussions, participatory rural appraisal and field observations. The study revealed that the most remarkable local institutions connected to forest biodiversity management include： Village Natural Resources Man- agement Committee （92%）, tree nursery group （79.4%）, beekeep- ing groups （61.1%）, fish fanning （43.3%）, livestock rearing group （33.9%）. Main activities carried out by local institutions which directly contribute to the sustainability Of forest reserve include： forest patrols, fire extinguish, preparation of fire breaks, plant- ing of trees along the forest boundaries, creation of awareness, arresting of forest defaulters, participation in income generation activities. For the purpose of realization that local communities are capable of managing forest biodiversity through their traditional institutions, the policy should provide tangible opportunity for local communities to meet their needs as they manage the forests.

Forest cover change and its effects on the livelihood of the dependent local people:the case of Sesheke district of Zambia

Objective-To investigate forest cover change in Masese Local Forest Reserve and its effects on the livelihoods of the dependent communities;to establish the occurrence of forest cover change in Masese Local Forest Reserve;to determine the extent of forest cover change in Masese from 1990to 2005;to determine the tree species that have been affected by forest cover change in Masese; and to assess the effects of forest cover change on the livelihoods of the dependent communities. Methods-Interviews and questionnaire were conducted with a proportion of 36households from Maondo and 84households from Mulimambango settlements.Scenes of landsat images of 1990,2000, 2005and Earth Google image for Masese were used for map analysis.Also remote sensing was used to analyze landsat images and Google image to detect forest and non-forest classes.Results and Conclusion-Forest cover change has adverse implication on the provision of wood forest products and nonwood forest products to the dependent local communities.The declining status of dominant Baikiaea Forest that has exploitable species for building materials and fuel wood has affected the livelihoods of the dependent local communities.There is also increased cost and shortage of fire wood and building materials due to deforestation in Masese Forest Reserve.

Estimation of Economic Value of Agroforestry Systems at the Local Scale in Eastern Sudan

The objective of this paper is to institute farmers’ own perceptions of the on-and off-farm benefits of agroforestry systems (AFS). Using use value approach, this paper presents empirical evidence on the use values of three types of AFS practiced by the refugees and their hosting communities in Eastern Sudan. The total economic value (TEV) was applied as a framework to estimate the ecosystem values of AFS under study. Goods values were estimated using specific market values, while the services values were qualitatively described according to local perceived values of the local communities. Perceived TEV of AFS includes marketable and non-marketable goods and services. The main direct marketable and sustainable high value products include: food, cash crops, firewood, gum, fodder, NTFPs medicine, fodder, and honey. The valuation results reveal that AFS in the project sites have significantly contributed to the livelihoods of the local communities. Overall, the average net direct-use value of marketable products across all sites was estimated at 7,346,000.0 SDG (1,335,636.36 US$) HH/annum. Gum Arabic alone accounted for 38%, followed by sorghum grain and fodder 35%, and cash crops (sesame) 18%. This value would be many time higher if other indirect values (non-marketable) services such as shade, aesthetic and recreation, environmental protection, biodiversity and carbon sequestration are quantified. The goods and services mentioned above provide sustainable income to the farmer directly and viable benefits to the region indirectly. Hence, AFS in the study sites shows the way to reconcile two conflicting goals: short-term food and livelihood needs with long-term environmental conservation and improvement. The study provides evidence that the high local perceived values of AFS in the study sites constitute a central means of livelihood, whereas its contribution to the local economy. The study stresses the need to quantify the monetary values of non-marketed products to consistently account for resource availability and usage to further sound policy decisions. Tenure security, farmer support services and human capital development were major areas identified for policy development.

Local People＇s Perception of Forest Resources Conservation in Ekiti State, Nigeria

This study examines local people＇s perception of forest resources （FR） conservation around two plantation forest reserves （PFR） and two natural forest reserves （NFR） in Ekiti State in order to determine the factors that can contribute to sustainable FR conservation. Questionnaire and interview were used to collect data from 240 respondents. Data were analyzed using descriptive and inferential statistics. 75.0% and 86.1% of respondents around PFR recognized the importance of conserving the FR for economic benefits and biodiversity respectively, while 66.7% would not want the FR conserved for cultural values. 82.9% of respondents around NFR would want the FR conserved for economic benefits, while 74.3% and 66.7% would not want the forest conserved for cultural values and biodiversity respectively. For efficient conservation, participation in forest management and involvement in decision making with means of 3.45 and 3.52 ranked highest in PFR and NFR respectively. Probit regression analysis showed that in PFR and NFR, age, education and income were positively significant to FR conservation （p 〈 0.05）. Creating an enabling environment that will make local people appreciate historical cultural values of the forest for tourism is essential for efficient FR conservation in the study area.

Comparison of the local pivotal method and systematic sampling for national forest inventories

Background:The local pivotal method(LPM)utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories(NFIs).Its performance compared to simple random sampling(SRS)and LPM with geographical coordinates has produced promising results in simulation studies.In this simulation study we compared all these sampling methods to systematic sampling.The LPM samples were selected solely using the coordinates(LPMxy)or,in addition to that,auxiliary remote sensing-based forest variables(RS variables).We utilized field measurement data(NFI-field)and Multi-Source NFI(MS-NFI)maps as target data,and independent MS-NFI maps as auxiliary data.The designs were compared using relative efficiency(RE);a ratio of mean squared errors of the reference sampling design against the studied design.Applying a method in NFI also requires a proven estimator for the variance.Therefore,three different variance estimators were evaluated against the empirical variance of replications:1)an estimator corresponding to SRS;2)a Grafström-Schelin estimator repurposed for LPM;and 3)a Matérn estimator applied in the Finnish NFI for systematic sampling design.Results:The LPMxy was nearly comparable with the systematic design for the most target variables.The REs of the LPM designs utilizing auxiliary data compared to the systematic design varied between 0.74–1.18,according to the studied target variable.The SRS estimator for variance was expectedly the most biased and conservative estimator.Similarly,the Grafström-Schelin estimator gave overestimates in the case of LPMxy.When the RS variables were utilized as auxiliary data,the Grafström-Schelin estimates tended to underestimate the empirical variance.In systematic sampling the Matérn and Grafström-Schelin estimators performed for practical purposes equally.Conclusions:LPM optimized for a specific variable tended to be more efficient than systematic sampling,but all of the considered LPM designs were less efficient than the systematic sampling design for some target variables.The Grafström-Schelin estimator could be used as such with LPMxy or instead of the Matérn estimator in systematic sampling.Further studies of the variance estimators are needed if other auxiliary variables are to be used in LPM.

Contribution of Sumalindo Company:In Managing Forest Resources with Local Communities:Mahakam Ulu-East Kalimantan

The role of HPH(Forest Logging Concession)in developing rural communities is very significant.SLJ(Sumalindo Lestari Jaya)as HPH company has an important contribution in empowering local communities,especially in opening land transportation in the interior and helping to build agriculture and gardens.The existence of Sumalindo company participates in developing forest resource management with local communities,among others,increasing livelihoods,maintaining and developing biodiversity conservation and maintaining climate change.These efforts are in accordance with the regulations of the KLHK(Ministry of Environment and Forestry),that every HPH holder is required(mandatory)to obtain a certificate of“PHAPL”(Sustainable Production Natural Forest Management)and an“eco label”from the Indonesian Eco Label Institute.Besides,it is recommended that the holders of HPH concessions and HTI(Industrial Timber Plantations)have an FSC(Forest Stewardship Council)certificate from the EU(European Union),and must meet three indicator elements,namely economic,social and ecological in SFM(Sustainable Forest Management).This article examines three critical questions that show the role of Sumalindo Company in economic,ecological and social development and managing forest resources with the community as follows:(1)The role of Sumalindo company contributes to the development of road infrastructure in the interior;(2)The role of Sumalindo in improving livelihoods and economic and social empowerment of local communities;(3)The role of Sumalindo with local communities in managing forest resources,including maintaining and developing biodiversity conservation and maintaining climate change.

Fine-grained grid computing model for Wi-Fi indoor localization in complex environments

The fingerprinting-based approach using the wireless local area network(WLAN)is widely used for indoor localization.However,the construction of the fingerprint database is quite time-consuming.Especially when the position of the access point(AP)or wall changes,updating the fingerprint database in real-time is difficult.An appropriate indoor localization approach,which has a low implementation cost,excellent real-time performance,and high localization accuracy and fully considers complex indoor environment factors,is preferred in location-based services(LBSs)applications.In this paper,we proposed a fine-grained grid computing(FGGC)model to achieve decimeter-level localization accuracy.Reference points(RPs)are generated in the grid by the FGGC model.Then,the received signal strength(RSS)values at each RP are calculated with the attenuation factors,such as the frequency band,three-dimensional propagation distance,and walls in complex environments.As a result,the fingerprint database can be established automatically without manual measurement,and the efficiency and cost that the FGGC model takes for the fingerprint database are superior to previous methods.The proposed indoor localization approach,which estimates the position step by step from the approximate grid location to the fine-grained location,can achieve higher real-time performance and localization accuracy simultaneously.The mean error of the proposed model is 0.36 m,far lower than that of previous approaches.Thus,the proposed model is feasible to improve the efficiency and accuracy of Wi-Fi indoor localization.It also shows high-accuracy performance with a fast running speed even under a large-size grid.The results indicate that the proposed method can also be suitable for precise marketing,indoor navigation,and emergency rescue.

Planting position and shade enhance native seedling performance in forest restoration for an endangered malagasy plant

The critically endangered tree Schizolaena tampoketsana is confined to a few diminished and degraded forest fragments on the Malagasy highlands. This habitat is vulnerable to loss due to frequent fires in the surrounding grassland that threaten to spread into the forest. One of these fragments is the focus a conservation project and here the managers aim to conserve S. tampoketsana by restoring its forest habitat to its former extent as evidenced by remnant woody plants. To inform this activity the survival and early-stage growth of seedlings of four locally native tree species were compared under contrasting conditions of proximity to the remaining forest and shade. After 12 months, seedlings of three species(Baronia taratana, Eugenia pluricymosa, Uapaca densifolia) survived better and experienced improved growth in height in grassland close to the existing forest rather than distant from it, and two survived better with shade rather than unshaded. A number of mechanisms could explain these results including reduced exposure to desiccating sunlight and winds and better soil and greater water availability close to the forest. The seedlings of one species(Nuxia capitata) survived well under all conditions. This study suggests that reforestation in these dry highlands is most feasible adjacent to remnant forest fragments and in microhabitats that minimize water loss, though young plants of some tree species may be capable of surviving in harsher conditions.

RANDOM FOREST FOR INTERMEDIATE DESCRIPTOR FUSION IN SHOT BOUNDARY DETECTION

Shot boundary detection is the fundamental part in many real applications as video retrieval and so on. This paper tackles the problem of video segment obtaining in complex movie videos. Firstly, intermediate descriptor is proposed to depict the variation of both abrupt and gradual change in shot boundaries, which is formed by distance vector on Local Binary Pattern(LBP), GIST(GIST) or their fusion. Instead of just using the adjacent frames distance, intermediate descriptor keeps the distances between current frame and consecutive frames. It comprehensively characterizes local temporal structure, which is especially important for gradual change. For the excellent ability for feature fusion in random forests, it is adopted here to verify the fusion effect of intermediate descriptor on LBP and GIST. The whole experiments are designed on the subset of TRECVid 2013 INS(INstance Search) task to verify the effectiveness of proposed intermediate descriptor and the fusion ability for random forest. Compared with static and adaptive thresholds approaches, the best performance can be achieved by post-fusion of intermediate descriptor on LBP and GIST.

基于iForest和LOF的流量异常检测

异常检测在现代大规模分布式系统的安全管理中起着重要作用,而网络流量异常检测则是组成异常检测系统的重要工具。网络流量异常检测的目的是找到和大多数流量数据不同的流量,并将这些离群点视为异常。由于现有的基于树分离的孤立森林(iForest)检测方法存在不能检测出局部异常的缺陷,为了克服这个缺陷,提出一种基于iForest和局部离群因子(LOF)近邻集成的无监督的流量异常检测方法。首先,改进原始的iForest与LOF算法,在提升检测精度的同时控制算法时间;然后分别使用两种改进算法进行检测,并将结果进行融合以得到最终的检测结果;最后在自制数据集上对所提方法进行有效性验证。实验结果表明,所提方法能够有效地隔离出异常,获得良好的流量异常检测效果。

Constraints to Tropical Forest Conservation and Successful Monitoring and Assessment of Land Uses Cover and Change: Do the Forest Definition and Administration Really Matter?

We examine the constraints to conservation and to successful forestlands’ monitoring/assessments in central Togo through GIS spatial analyses and through a critical overview of the current forestry administration’s model. The major findings are that the land classification based on few inventory parameters cannot substitute for “what forest is”, rather these inventory parameters constitute a mean to sound forest management and conservation when relevantly decided. Also as these parameters measured from satellite imagery are supplemented by continuous fine management data they may consistently contribute to the classification of the vegetation cover. This helps to suggest that solution to forest degradation/deforestation, and monitoring/ assessment requires data refinement through local forest management. Else, the actual forestry administration is local communities and indigenous people’s needs biased because it has been negligent of the cultural forestry practices, the major constraints to conservation and the monitoring/assessment of forest lands. As a common pool-resource, the questions relative to forest cannot be addressed at a single environmental concerns level. Interests are multiple and various along the spectrum from the global environment level to the local environmental level that should be accounted for. Thus we recommend a reconsideration of the forestry administration model. What is required are simple policies processes to define forest management plans that promote simultaneously sustainable forest management while accounting for any stakeholder concern, importantly the cultural forestry that addresses specific local communities and indigenous people’s forest related interests.

3-D Grid-Based Localization Technique in Mobile Sensor Networks

Considering the environmental protection, forest fire becomes a more and more serious problem and requires more concerns. This paper provides an efficient method for fire monitoring and detection in forests using wireless sensor network technology. The proposed technique estimates the location of a sensor node based on the current set of hop-count values, which are collected through the anchor nodes’ broadcast. Our algorithm incorporates two salient features;grid-based output and event-triggering mechanism, to improve the accuracy while reducing the power consumption. Through the computer simulation, the output region obtained from our algorithm can always cover the target node. In addition, the algorithm was implemented and tested with a set of Crossbow sensors. Experimental results demonstrated the high feasibility and worked well in real environment.

Industrial Centric Node Localization and Pollution Prediction Using Hybrid Swarm Techniques

Major fields such as military applications,medical fields,weather forecasting,and environmental applications use wireless sensor networks for major computing processes.Sensors play a vital role in emerging technologies of the 20th century.Localization of sensors in needed locations is a very serious problem.The environment is home to every living being in the world.The growth of industries after the industrial revolution increased pollution across the environment.Owing to recent uncontrolled growth and development,sensors to measure pollution levels across industries and surroundings are needed.An interesting and challenging task is choosing the place to fit the sensors.Many meta-heuristic techniques have been introduced in node localization.Swarm intelligent algorithms have proven their efficiency in many studies on localization problems.In this article,we introduce an industrial-centric approach to solve the problem of node localization in the sensor network.First,our work aims at selecting industrial areas in the sensed location.We use random forest regression methodology to select the polluted area.Then,the elephant herding algorithm is used in sensor node localization.These two algorithms are combined to produce the best standard result in localizing the sensor nodes.To check the proposed performance,experiments are conducted with data from the KDD Cup 2018,which contain the name of 35 stations with concentrations of air pollutants such as PM,SO_(2),CO,NO_(2),and O_(3).These data are normalized and tested with algorithms.The results are comparatively analyzed with other swarm intelligence algorithms such as the elephant herding algorithm,particle swarm optimization,and machine learning algorithms such as decision tree regression and multi-layer perceptron.Results can indicate our proposed algorithm can suggest more meaningful locations for localizing the sensors in the topology.Our proposed method achieves a lower root mean square value with 0.06 to 0.08 for localizing with Stations 1 to 5.

Improved allometric equations for tree aboveground biomass estimation in tropical dipterocarp forests of Kalimantan,Indonesia

Background： Currently, the common and feasible way to estimate the most accurate forest biomass requires ground measurements and allometric models.Previous studies have been conducted on allometric equations development for estimating tree aboveground biomass（AGB） of tropical dipterocarp forests（TDFs） in Kalimantan（Indonesian Borneo）.However, before the use of existing equations, a validation for the selection of the best allometric equation is required to assess the model bias and precision.This study aims at evaluating the validity of local and pantropical equations; developing new allometric equations for estimating tree AGB in TDFs of Kalimantan; and validating the new equations using independent datasets.Methods： We used 108 tree samples from destructive sampling to develop the allometric equations, with maximum tree diameter of 175 cm and another 109 samples from previous studies for validating our equations.We performed ordinary least squares linear regression to explore the relationship between the AGB and the predictor variables in the natural logarithmic form.Results： This study found that most of the existing local equations tended to be biased and imprecise, with mean relative error and mean absolute relative error more than 0.1 and 0.3, respectively.We developed new allometric equations for tree AGB estimation in the TDFs of Kalimantan.Through a validation using an independent dataset,we found that our equations were reliable in estimating tree AGB in TDF.The pantropical equation, which includes tree diameter, wood density and total height as predictor variables performed only slightly worse than our new models.Conclusions： Our equations improve the precision and reduce the bias of AGB estimates of TDFs.Local models developed from small samples tend to systematically bias.A validation of existing AGB models is essential before the use of the models.

现代化生态文明建设中的林长制治理探析

林长制将保护发展森林草原资源落实为地方党政领导干部的主体责任,“属地管理,分级负责”作为一种重要的制度,是我国现代化生态文明建设不可或缺的组成部分。林长制以习近平生态文明思想为引领,具有特定的理论基础,全面推行林长制对现代化生态文明建设的意义重大。论文通过对林长制治理地方实践的考察,对标林长制有关法律法规、林长制职权范围、林长制考核和激励机制、林长制监督体系,分析林长制治理中存在的问题,最后提出了优化林长制治理的对策。

耦合DWT-IFLOF的大坝监测数据异常检测算法

基于数据驱动的模型已广泛应用于大坝运行状态建模与短期变形预测等领域中,而监测数据中存在的异常值会削弱甚至破坏数据驱动模型的可信度和鲁棒性。针对上述问题,提出一种耦合DWT-IFLOF的大坝监测数据异常检测算法。首先,采用小波降噪技术减少监测数据集中采集噪声对模型建模的负面干扰。其次设计一种耦合孤立森林(iForest)异常检测算法与归一化局部离群因子值(LOF_(nor))的全新监测数据异常度量化表达式。最后通过引入拉伊达准则,依据计算得到的异常分数,对异常值进行定性筛查。试验结果表明,相较于热门异常检测算法,在查全率层面提升18.32%以上;查准率提升20.14%以上;准确率提升0.71%以上。可针对大坝安全监测数据中的异常值进行有效检测。

Biodiversity responses to insular fragmentation in Amazonia: Two decades of research in the Balbina Hydroelectric Reservoir

As hydropower development expands across lowland tropical forests,flooding and concomitant insular fragmentation have become important threats to biodiversity.Newly created insular landscapes serve as natural laboratories to investigate biodiversity responses to fragmentation.One of these most iconic landscapes is the Balbina Hydroelectric Reservoir in Brazilian Amazonia,occupying>400000 ha and comprising>3500 forest islands.Here,we synthesise the current knowledge on responses of a wide range of biological groups to insular fragmentation at Balbina.Sampling has largely concentrated on a set of 22 islands and three mainland sites.In total,39 studies were conducted over nearly two decades,covering 17 vertebrate,invertebrate,and plant taxa.Although species responses varied according to taxonomic group,island area was consistently included and played a pivotal role in 66.7%of all studies examining patterns of species diversity.Species persistence was further affected by species traits,mostly related to species capacity to use/traverse the aquatic matrix or tolerate habitat degradation,as noted for species of vertebrates and orchid bees.Further research is needed to improve our understanding of such effects on wider ecosystem functioning.Environmental Impact Assessments must account for changes in both the remaining habitat amount and configuration,and subsequent long-term species losses.