The use of Bacillus thuringiensis on Forest Integrated Pest Management

Bacillus thuringiensis is a major microbial insecticide and a source of genes encoding several proteins toxic to insects. In this paper the authors g ive a brief summary of Bacillus thuringiensis used on the integrated pest manage ment in forestry. The derivatives of Bt strain HD1 subsp kurstaki have been wide ly used to control the forest pests such as the gypsy moth (Lymantria dispar), s pruce budworm (Choristoneura fumiferana), the pine processionary moth (Thaumetop oea pityocampa), the European pine shoot moth (Rhyacionia buoliana) and the nun moth (Lymantria monacha). Some progresses of transferring and expressing Bt toxi n gene in forest trees are offered with a discussion on the limits and future pr ospects of using Bt products in forestry.

Integrated approach for understanding spatio-temporal changes in forest resource distribution in the central Himalaya

Intense anthropogenic exploitation has altered distribution of forest resources. This change was analyzed using visual interpretation of satellite data of 1979, 1999 and 2009. Field and interactive social surveys were conducted to identify spatial trends in forest degradation and data were mapped on forest cover and land use maps. Perceptions of villagers were compiled in a pictorial representation to understand changes in forest resource distribution in central Himalaya from 1970 to 2010. For- ested areas were subject to degradation and isolation due to loss of con- necting forest stands. Species like Lantana camara and Eupatorium adenophorum invaded forest landscapes. Intensity of human pressure differed by forest type and elevation. An integrated approach is needed to monitor forest resource distribution and disturbance.

An integrated method for matching forest machinery and a weight-value adjustment

Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.

Multi-modal Gesture Recognition using Integrated Model of Motion, Audio and Video

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Study on Integration of Suburban Forest Park and Eco-city into “Mega-landscape”

On the basis of analyzing the development of suburban forest parks, the paper proposed the combination of eco-city construction and suburban forest parks, and the construction of "mega-landscape" mode, which offers a new concept for the development of suburban forest parks.

Changing Forestry Policy by Integrating Water Aspects into Forest/Vegetation Restoration in Dryland Areas in China

Restoration forestry （forest rehabilitation） or re-vegetation is one effective measure to solve environmental problems, notably soil erosion. It may be further stimulated by the Clean Development Mechanism for carbon sequestration. However, there is an intensive and on-going debate about the adverse effects arising from afforestation in dryland areas, such as soil drying up which may cause further damage to the success of forest restoration, and the water yield reduction from watershed which may harm the regional development. On other hand, some preliminary studies showed a possibility that these adverse effects may be diminished more or less by properly designing the system structure and spatial distribution of forest/vegetation in a watershed. However, it is urgent to develop an evidence-based and sustainable new forestry policy for harmonizing forest-water interrelation. As a leading country in afforestation, China is beginning to develop a more trans-disciplinary and cross-sectoral forestry policy for harmonizing forestry development with water management. The main points of the changing new forestry policy should include： （1） Establishing a regional development strategy focusing on harmonized forest-water relations; （2） Taking forest-water interactions as an important part of evaluation; （3） Reducing the ＇eco-water＇ quota of forests through technical advancement; （4） Developing and extending water-adaptive forest management practices; （S） Strengthening forest ecohydrological research and decision support ability.

Turkey Creek—A Case Study of Ecohydrology and Integrated Watershed Management in the Low-Gradient Atlantic Coastal Plain, USA

Water yield, water supply and quality, wildlife habitat, and ecosystem productivity and services are important societal concerns for natural resource management in the 21st century. Watershed-scale ecohydrologic studies can provide needed context for addressing complex spatial and temporal dynamics of these functions and services. This study was conducted on the 5240 ha Turkey Creek watershed (WS 78) draining a 3rd order stream on the Santee Experimental Forest within the South Carolina Atlantic Coastal Plain, USA. The study objectives were to present the hydrologic characteristics of this relatively undisturbed, except by a hurricane (Hugo, 1989), forested water-shed and to discuss key elements for watershed management, including water resource assessment (WRM), modeling integrated water resources management, environmental assessment, land use planning, social impact assessment, and information management. Runoff coefficients, flow duration curves, flood and low flow frequency curves, surface and ground water yields were assessed as elements of the WRM. Results from the last 10 years of interdisciplinary studies have also advanced the understanding of coastal ecohydrologic characteristics and processes, water balance, and their modeling including the need of high resolution LiDAR data. For example, surface water dynamics were shown to be regulated primarily by the water table, dependent upon pre- cipitation and evapotranspiration (ET). Analysis of pre- and post-Hugo streamflow data showed somewhat lower but insignificant (α = 0.05) mean annual flow but increased frequency of larger flows for the post-Hugo compared with the pre-Hugo level. However, there was no significant difference in mean annual ET, potentially indicating the resiliency of this coastal forest. Although the information from this study may be useful for comparison of coastal ecohydrologic issues, it is becoming increasingly clear that multi-site studies may be warranted to understand these complex systems in the face of climate change, sea level rise, and increasing development in coastal regions.

Ecotourism Development in the Context of Cultural and Tourism Integration:A Case Study of Wanli Mopan Mountain Forest Park

The integration of culture and tourism is a new form of tourism and a trend of tourism industry development.Mopan Mountain Forest Park in Wanli District of Nanchang City is taken as research object,and the excavation of its cultural elements is analyzed.It is thought that cultural elements can revitalize the culture and tourism industry,promote the integration of culture and tourism,encourage the mutual penetration of cultural innovation,design services and tourism products,improve the development and service level of cultural tourism products,and accelerate the development of characteristic cultural tourism.

Intelligent Deep Learning Enabled Wild Forest Fire Detection System

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.

中国造纸业绿色战略演进历程

中国造纸业绿色战略的实践从萌芽期算起已经走过了60年艰难而富有成效的发展历程。在当今国家生态文明建设和实现双碳目标的背景下,对中国造纸业绿色发展过程进行回顾和总结,挖掘绿色战略的演进规律,并预估未来的战略趋势是十分必要的。根据绿色经济和绿色战略理论,以及可再生资源型企业绿色战略演进的一般规律,本文对中国造纸业绿色战略实践的重要事件和举措进行系统梳理,发现中国造纸业绿色战略总体上经历了开环和闭环绿色战略两大阶段。其中,开环绿色战略阶段包含原料导向(林纸一体化)绿色战略和末端治理绿色战略;闭环绿色战略阶段包含循环绿色战略和“循环+”绿色战略。据此,运用超循环经济理论,可以预计中国造纸业绿色战略的未来发展趋势,即林纸超循环绿色战略。

整体性保护视野下文化景观遗产地产业发展策略研究--以景迈山为例

文化景观保护的理论和实践都强调将人和非物质要素纳入到遗产的整体性保护之中。遗产地的产业发展方式深刻影响着遗产保护效果。普洱景迈山古茶林文化景观遗产地的产业发展因申遗成功迎来新的机遇,但由于整体性保护理念在制度中并未得到充分明确且在实践中认识不足,遗产地产业发展重点偏向物质要素而忽略了非物质要素,导致茶产业发展思路和村寨利用方式与遗产保护目标契合度不够,文旅产业偏向观光而没有全面展示遗产内涵,非物质文化遗产传承面临断层风险,影响了遗产地可持续发展的文化根基。挖掘非物质要素的产业价值,以整体性保护视角重构产业发展思路,构建“践行传统生产生活赋能产业发展”的良性循环,并在制度上明确整体性保护理念、完善产业发展引导和扶持规范,或许是化解遗产地发展需求与遗产保护间矛盾的可行策略。

竹笋采挖下克隆整合对毛竹林发笋成竹规律的影响

【目的】为研发毛竹林高产高效生态经营技术提供一定参考。【方法】调查浙西南地区采挖毛竹林竹笋后的笋-幼竹生长过程,通过存活曲线分析毛竹林挖笋后的发笋成竹规律,探讨挖笋对竹笋中单宁、粗脂肪、粗蛋白等品质指标的影响。【结果】竹笋采挖提高了毛竹林地的发笋能力,挖笋样地的发笋数比未挖笋样地增加了12.8%(P<0.05),而挖笋后选留竹笋的存活率也显著高于未挖笋样地;与未挖笋样地相比,挖笋样地内毛竹新分株的平均胸径并未发生显著改变(P>0.05),挖笋不会降低新分株胸径而使林分衰退;竹笋间的非对称性竞争有利于竹笋地径的径级为Ⅰ-Ⅲ级竹笋的生长与存活,随着地径的提高竹笋死亡率显著降低,而径级Ⅳ级以上竹笋则有着较高的死亡率。盛笋早期以后,径级相对较小(Ⅳ级以上)的竹笋开始大量萌发,这类竹笋若不及时采挖,大部分会出现退笋,造成资源浪费;挖笋和未挖笋样地竹笋的含水率、蛋白质和粗脂肪含量在各笋期均未见显著差异(P>0.05),尽管挖笋样地竹笋的单宁含量在末笋期显著高于未挖笋样地,但两种样地其他笋期单宁含量均未见显著差异。【结论】毛竹林竹笋的采挖,可缓解竹笋间的非对称性的资源竞争,有效避免大量退笋导致的毛竹母株营养消耗,实现母株资源的克隆整合,增加竹笋产量。因此,合理的竹笋采挖有利于毛竹笋用林的高效生产及可持续性经营。

基于大数据流水线系统的算法模型整合方法研究——以基于机器学习方法的LiDAR数据树木生物量反演为例

【背景】激光雷达(LiDAR)数据在森林资源分析利用方面有着广泛应用,科研人员研制了很多涉及大数据管理和人工智能的专业算法模型,这些算法模型目前多数散落在研究人员手里,尚缺乏新型信息化平台对其进行整合。【方法】大数据流水线系统πFlow软件具有大数据管理能力和大数据算法集成能力,并可以所见即所得方式构建流水线并调度运行流水线,适合于LiDAR数据复杂算法模型的整合,且流水线可定制、可复用。【内容】本文介绍了πFlow的特点和功能,并以基于LiDAR冠层高度模型(CHM)数据的树冠解析及利用机器学习方法估测树木生物量为例,介绍了将算法整合到πFlow并构建LiDAR数据分析处理流水线的方法和技术,且对流水线进行了测试运行。【结果】利用πFlow构建的可重复信息化平台可支撑野外站观测网络的LiDAR数据生物量快速反演,为数据密集型的专业数据处理算法模型的整合提供了创新方法技术。

数字经济下福建森林旅游与乡村振兴的融合发展

基于新古典经济学、文化生态、社会资本和环境经济学等相关理论,结合福建5G+平安鼓岭项目、智能导览典型案例、旅游元宇宙城市等数字化实践,探讨森林旅游和乡村振兴在经济、文化、社会及生态系统等方面融合发展的理论逻辑。结果表明:数字技术的应用优化了市场资源配置,加强了文化和社会联系,提升了生态系统的可持续性;数字经济下森林旅游与乡村振兴融合发展存在数字化森林生态模式、个性化大数据森林导览模式、数字森林产品电商销售模式、虚拟森林生态体验模式和社交媒体森林旅游推广模式5种可行模式。因此,为了推动福建省森林旅游与乡村振兴智能、高效、可持续地融合发展,应加强建设数字基础设施,努力提升居民数字素养,不断完善数字法律法规。

基于改进的随机森林—模糊积分模型的家庭农牧场信用评级研究

缓解融资难融资贵问题是实现家庭农牧场可持续发展的关键,而构建家庭农牧场信用评级体系是解决该难题的基础。针对家庭农牧场信用风险评估中样本数据指标多、噪声复杂、非线性乃至高维度等问题,以内蒙古自治区12个盟市500个家庭农牧场为信用评价对象,将XGBoost算法、随机森林算法、模糊积分模型进行组合,构建了改进的随机森林—模糊积分模型,对家庭农牧场进行信用评级。分析结果表明:运用改进的随机森林—模糊积分模型对家庭农牧场进行信用评级的准确率、精确率、召回率、F1分数更高。

山水林田湖草沙系统治理与水土保持高质量发展

[目的]中国水土流失治理已由“全面治理,重点治理”迈向“系统治理,攻坚克难”的新阶段。分析山水林田湖草沙系统治理的内涵、准则及其与水土保持的关系,旨在丰富新时代水土保持理论体系,引领水土保持高质量发展。[方法]在长期理论探索和实践验证的基础上,梳理山水林田湖草沙系统治理理念的发展过程,阐明其内涵、目标与实践准则。[结果]水土流失长期治理实践总结提升形成的以小流域为单元的综合治理技术路线是山水林田湖草沙生命共同体系统思想最朴素的实践体现。小流域综合治理的系统性主要体现为治理对象的系统协调,总体布局的系统统筹,治理措施的系统考量,治理成效的多效益兼顾,实施和管理的多部门协同和多主体参与的共治共享6个方面。水土保持高质量发展实践需要遵循的基于系统治理理念的具体举措包括:利用系统思维理解水土保持高质量发展的内涵和要求,精准诊断山水林田湖草沙系统短板及其控制性要素,构建山水林田湖草沙多层次全方位立体化防控体系,构筑完备的水土保持管理与技术保障体系。[结论]在新的历史时期,应该完整准确理解并全面贯彻落实山水林田湖草沙系统治理的理念,探索整体提升水土保持学术研究水平和治理效能的新路径、新模式、新机制。同时应结合区域或流域实际,对农田、水利、牧业、林业及生产建设活动进行全面综合系统的规划和治理,推动水土保持高质量发展。

基于生态韧性的山水林田湖草沙一体化保护修复框架

基于生态韧性内涵的山水林田湖草沙一体化保护修复是提升区域生态系统承载力和风险适应性的创新路径。本文阐述了生态韧性内涵与山水林田湖草沙生命共同体的特征,明确了一体化生态修复同生态韧性内涵关联逻辑,构建了山水林田湖草沙一体化保护修复的韧性作用机制和“问题识别-要素分析-策略制定”研究框架。以石家庄市为例,识别了其水土流失、湿地萎缩等生态问题,明确流域单元关键生态要素,并基于石家庄市生态系统地理空间格局以及面临的生态风险,提出调田节水、生境修复、林草保育等保护策略。以期为推进山水林田湖草沙系统修复工作以及增强生态系统应对干扰的抵抗力和适应力提供支撑。

基于机器学习算法的森林生物量多源遥感估测

为进一步探索不同空间分辨率影像在10 m×10 m样地尺度下森林生物量估测性能及协同机器学习算法(RF、SVM、DT、GBM、k-NN、Stacking)的估测效果,利用光学遥感GF2(高分二号卫星)、sentinel 2A、Landsat 8 OLI、SUM(整合3种遥感数据源)影像及辅助变量DEM高程数据、环境因子、林分因子(森林类型、优势树种),在Boruta算法变量选择下用机器学习算法对元谋地区乔木林森林生物量(地上+地下)进行遥感估测,并比较4种影像下的估测精度。研究表明:(1)基于Boruta算法分别对3种影像及整合3种影像条件下进行变量选择,单一影像中sentinel 2A的植被指数PEIP、Landsat 8 OLI的纹理因子b2_ME_9×9、GF2的GNDVI分别为3种影像下的最高得分变量,多源融合估测森林生物量中GF2的GNDVI为最佳得分变量;(2)基于Boruta算法选择的变量构建RF、SVM、DT、GBM、k-NN算法以及对5个模型的Stacking集成算法,SUM的Stacking集成算法的估测效果最优,模型决定系数(R2)为0.73,均方根误差(RMSE)为28.46 t·hm^(-2),集成算法下的SUM的估测性能优于sentinel 2A、Landsat 8 OLI,GF2优于sentinel 2A,sentinel 2A的估测性能优于Landsat 8 OLI。研究结果说明在生物量遥感估测中高分辨率影像具有较好的估测效果,同时多源遥感协同估测、集成算法均可提高森林生物量遥感估测精度,可为森林生物量遥感估测提供参考和借鉴。

基于Stacking集成学习的枣树智能灌溉系统设计与试验

南疆降雨量少,气候干燥,农业用水紧张,水资源节约尤为重要,针对此问题设计一套智能灌溉系统。系统使用阿里云服务器作为上位机,树莓派作为下位机,并搭建相应的操作页面。根据Penman-Monteith公式中需要的气象数据、过去7天需水量以及前1天气象数据为输入向量,作物需水量为输出向量,构建基于随机森林、BP神经网络与岭回归的Stacking集成学习预测模型。结果表明Stacking集成学习预测模型拟合系数R 2为0.973,且MAE、RMSE、MAPE三类误差更小,Stacking集成学习预测模型预测效果更强。灌溉试验中自动灌溉决策正确,系统运行稳定,为新疆地区农业提高水资源利用问题提供思路。

种植绿肥对我国水稻产量和土壤肥力影响的整合分析

为探究种植绿肥对水稻产量和土壤肥力的影响以及为水稻增产稳产和土壤改良提供科学依据。对已发表的相关文献数据进行了收集,建立了362组包含种植绿肥(GM)和冬闲田(FFP)处理下水稻产量和土壤肥力的数据库。采用整合分析的方法,定量绿肥在不同地区、水稻种植模式、土壤性质、氮肥用量、绿肥种类下对水稻产量及土壤肥力的提升幅度,采用随机森林模型探究影响绿肥效应的主控因素。研究结果发现,在不同地区下,GM处理对土壤有机质含量的提升在南方稻区最大(21.17%)。在不同水稻种植模式下,GM处理对水稻产量和土壤肥力的提升幅度均表现为双季稻>单季稻;土壤全氮含量≤1.5 g/kg、有机质含量≤20 g/kg时对产量的提升幅度较高;当GM处理的施氮量≤150 kg/hm^(2)时对产量和土壤有机质含量的提升幅度均较高,分别为12.47%和22.36%,但是随着施氮量的逐渐增加,GM处理的增产幅度下降。不同绿肥种类下,GM处理对产量和土壤有机质含量的提升幅度有所差异,在产量提升方面,豆科绿肥(12.47%)>非豆科绿肥(7.22%)>混合绿肥(6.32%);对土壤有机质含量提升方面混合绿肥(12.69%)>非豆科绿肥(10.93%)>豆科绿肥(9.37%)。随机森林分析结果表明,在主控因素方面GM处理对水稻增产主要受土壤有机质含量、施氮量和有效磷含量(贡献率分别为18%、16%和15%)的影响,而GM提高有机质的影响因素主要有地区、速效钾和速效氮含量(贡献率分别为14%、12%和11%)。因此,GM能显著提高水稻产量和土壤肥力,尤其是在低肥力的土壤状况下GM处理对产量的提升幅度较好,GM与化肥配合使用能促进水稻增产和稻田土壤有机质含量的提升,但GM的施氮量不宜超过150kg/hm^(2),水稻和绿肥轮作长江流域稻区推荐豆科绿肥,而在南方稻区进行混合绿肥。