Which type of forest management provides most ecosystem services？

Background： Forest ecosystems are increasingly seen as multi-functional production systems, which should provide, besides timber and economic benefits, also other ecosystem services related to biological diversity, recreational uses and environmental functions of forests. This study analyzed the performance of even-aged rotation forest management （RFM）, continuous cover forestry （CCF） and any-aged forestry （AAF） in the production of ecosystem services. AAF allows both even-aged and uneven-aged management schedules. The ecosystem services included in the analyses were net present value, volume of harvested timber, cowberry and bilberry yields, scenic value of the forest, carbon balance and suitability of the forest to Siberian jay. Methods： Data envelopment analysis was used to derive numerical efficiency ratios for the three management systems. Efficiency ratio is the sum of weighted outputs （ecosystem services） divided by the sum of weighted inputs. The linear programing model proposed by Charnes, Cooper and Rhodes was used to derive the weights for calculating efficiency scores for the silvicultural systems. Results and conclusions： CCF provided more ecosystem services than RFM, and CCF was more efficient than RFM and AAF in the production of ecosystem services. Multi-objective management provided more ecosystem services （except harvested timber） than single-objective management that maximized economic profitability. The use of low discount rate （resulting in low cutting level and high growing stock volume） led to better supply of most ecosystems services than the use of high discount rate. RFM where NPV was maximized with high discount rate led to particularly poor provision of most ecosystem services. In CCF the provision of ecosystem services was less sensitive to changes in discount rate and management objective than in RFM.

Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms

Management of poultry farms in China mostly relies on manual labor.Since such a large amount of valuable data for the production process either are saved incomplete or saved only as paper documents,making it very difficult for data retrieve,processing and analysis.An integrated cloud-based data management system(CDMS)was proposed in this study,in which the asynchronous data transmission,distributed file system,and wireless network technology were used for information collection,management and sharing in large-scale egg production.The cloud-based platform can provide information technology infrastructures for different farms.The CDMS can also allocate the computing resources and storage space based on demand.A real-time data acquisition software was developed,which allowed farm management staff to submit reports through website or smartphone,enabled digitization of production data.The use of asynchronous transfer in the system can avoid potential data loss during the transmission between farms and the remote cloud data center.All the valid historical data of poultry farms can be stored to the remote cloud data center,and then eliminates the need for large server clusters on the farms.Users with proper identification can access the online data portal of the system through a browser or an APP from anywhere worldwide.

Information-Centric IoT-Based Smart Farming with Dynamic Data Optimization

Smart farming has become a strategic approach of sustainable agriculture management and monitoring with the infrastructure to exploit modern technologies,including big data,the cloud,and the Internet of Things(IoT).Many researchers try to integrate IoT-based smart farming on cloud platforms effectively.They define various frameworks on smart farming and monitoring system and still lacks to define effective data management schemes.Since IoT-cloud systems involve massive structured and unstructured data,data optimization comes into the picture.Hence,this research designs an Information-Centric IoT-based Smart Farming with Dynamic Data Optimization(ICISF-DDO),which enhances the performance of the smart farming infrastructure with minimal energy consumption and improved lifetime.Here,a conceptual framework of the proposed scheme and statistical design model has beenwell defined.The information storage and management with DDO has been expanded individually to show the effective use of membership parameters in data optimization.The simulation outcomes state that the proposed ICISF-DDO can surpass existing smart farming systems with a data optimization ratio of 97.71%,reliability ratio of 98.63%,a coverage ratio of 99.67%,least sensor error rate of 8.96%,and efficient energy consumption ratio of 4.84%.

Words apart:Standardizing forestry terms and definitions across European biodiversity studies

Forest biodiversity studies conducted across Europe use a multitude of forestry terms,often inconsistently.This hinders the comparability across studies and makes the assessment of the impacts of forest management on biodiversity highly context-dependent.Recent attempts to standardize forestry and stand description terminology mostly used a top-down approach that did not account for the perspectives and approaches of forest biodiversity experts.This work aims to establish common standards for silvicultural and vegetation definitions,creating a shared conceptual framework for a consistent study on the effects of forest management on biodiversity.We have identified both strengths and weaknesses of the silvicultural and vegetation information provided in forest biodiversity studies.While quantitative data on forest biomass and dominant tree species are frequently included,information on silvicultural activities and vegetation composition is often lacking,shallow,or based on broad and heterogeneous classifications.We discuss the existing classifications and their use in European forest biodiversity studies through a novel bottom-up and top-driven review process,and ultimately propose a common framework.This will enhance the comparability of forest biodiversity studies in Europe,and puts the basis for effective implementation and monitoring of sustainable forest management policies.The standards here proposed are potentially adaptable and applicable to other geographical areas and could be extended to other forest interventions.

Study on the Prediction System of Shrimp Field Distribution in the East China Sea Based on Big Data Analysis of Fishing Trajectories

In recent years,China has paid more and more attention to the development of marine economy and the management and protection of fishery resources.The management departments at all levels regulate and manage the fishing behavior of fishing vessels through the data of fishing trajectories.In this paper,the distribution of shrimp farms in the East China Sea is predicted by studying the trajectories and behavior patterns of shrimp boats in the system of fishing trajectories.At the same time,a set of shrimp farm distribution management system based on Back Propagation algorithm is established.It can monitor the trajectories of fishing boats and the distribution of shrimp groups in real time,which effectively improves the work efficiency and management mode of the management department.It also plays a positive role in regulating the behavior of fishing boats at sea.

Estimation of carbon storage of forest biomass for voluntary carbon markets:preliminary results

Estimating the carbon storage of forests is essential to support climate change mitigation and promote the transition into a low-carbon emission economy.To achieve this goal,voluntary carbon markets(VCMs)are essential.VCMs are promoted by a spontaneous demand,not imposed by binding targets,as the regulated ones.In Italy,only in Veneto and Piedmont Regions(Northern Italy),VCMs through forestry activities were carried out.Valle Camonica District(Northern Italy,Lombardy Region)is ready for a local VCM,but carbon storage of its forests was never estimated.The aim of this work was to estimate the total carbon storage(TCS;t C ha^−1)of forest biomass of Valle Camonica District,at the stand level,taking into account:(1)aboveground biomass,(2)belowground biomass,(3)deadwood,and(4)litter.We developed a user-friendly model,based on site-specifi c primary(measured)data,and we applied it to a dataset of 2019 stands extracted from 45 Forest Management Plans.Preliminary results showed that,in 2016,the TCS achieved 76.02 t C ha^−1.The aboveground biomass was the most relevant carbon pool(48.86 t C ha^−1;64.27%of TCS).From 2017 to 2029,through multifunctional forest management,the TCS could increase of 2.48 t C ha^−1(+3.26%).In the same period,assuming to convert coppices stands to high forests,an additional TCS of 0.78 t C ha^−1(equal to 2.85 t CO 2 ha^−1)in the aboveground biomass could be achieved without increasing forest areas.The additional carbon could be certifi ed and exchanged on a VCM,contributing to climate change mitigation at a local level.

Precision Livestock Farming: The Opportunities inPoultry Sector

Precision management of animals using technology is one innovation in agriculture that has the potential to revolutionizewhole livestock industries including the poultry sector. Limited research in precision livestock farming (PLF) in the poultry productionhas been so far conducted and most of them are conducted within the past 5-10 years. The PLF collects real-time data from individual orgroup of animals or birds using sensor technology, and involves the multidisciplinary team approach to give it a reality. Poultry scientistsplay a central role in executing poultry PLF with collaboration from agri-engineers and computer scientists for the type of measurementsto be made on biological or environmental variables. A real-time collection of environmental, behavioral and health data from birdgrow-out facilities can be a strong tool for developing daily action plans for poultry management. Unlike other livestock farming, theattributes of poultry rearing such as a closed housing system and vertically integrated industry provides a greater opportunity for poultrysector to adopt technology-based farming for enhanced production output.

森林生态产品价值实现的生态产业化经营实践与探索——以腾冲市沙坝国有林场为例

文章阐述了腾冲市沙坝国有林场探索森林生态产品价值实现的生态产业化经营实践现状,分析研究了其在资金、用地、经营权限、价值评估、收益分配等方面存在的问题,并提出了相关优化措施与政策建议,以期进一步提升生态产业化经营水平,促进以市场为主导的森林生态产品价值实现。

基于随机森林和最近邻插值法的交通流量数据修复方法

针对目前传感器在采集数据过程中由于受到天气或者自身设备故障等原因,造成数据缺失或者数据异常,导致不能从采集的数据中获得准确的交通变化规律等问题,分别提出基于改进最近邻插值算法和基于随机森林插补的交通流量数据缺失修复模型。由于交通数据缺失场景和缺失类型以及时空关联的差异性,将数据缺失类型划分为简单随机缺失和复杂连续缺失两种;利用改进的最近邻插值算法建立模型处理简单随机缺失,建立随机森林模型进行迭代插补处理复杂连续缺失;面对两种不同的数据缺失类型,利用期望最大化算法、深度信念网络、季节性差分自回归滑动平均模型分别搭建模型对比交叉验证改进的最近邻插值算法和随机森林插补方法。数据来源于美国加利福尼亚州PeMS(performance measurement system)实时采集的2022年6月1日—2022年7月31日以5 min为采样时间间隔的交通流量数据,为了模拟数据的缺失状况,将完整数据按照一定比例进行缺失,来模拟数据缺数的情况,得到简单随机缺失和复杂连续缺失分布的交通流量缺失数据集。结果表明:本实验在不同的缺失比例下均有良好的表现,通过设计不同的缺失比例和类型,各项评估指标均有明显优势,验证了两种数据缺失填充模型的有效性。

生态银行大数据平台赋能森林资源信息管理研究

本研究聚焦森林资源领域,通过分析福建顺昌、江西资溪、北京门头沟三地搭建的生态银行大数据平台中的森林资源管理利用模式,阐述顺昌县森林资源统计、资溪县林业金融创新、门头沟区林业碳汇交易案例。通过探索基于生态资源管理大数据平台建设推动森林资源管理的积极意义,为建设生态资源管理大数据体系提供参考。

基于云-边-端协同的区域级风电场大数据中心数据管理框架及优化运行方法

区域级风电场大数据中心面临运行能效低、交互性差、资源重复建设等问题,难以满足数字化特征凸显的新型电力系统对数据实时计算、绿色计算的需求。该文系统性梳理了风电场大数据中心典型数字化业务的类别、算力敏感性特征和可调节潜力,构建了基于云-边-端协同技术的数据管理架构,从数据交互、业务执行、资源调度和质量治理4个维度提出了大数据中心优化运行方法。算例仿真分析了所提架构在数据传输、存储和能耗等方面的性能,结果表明:相较于集中式架构,云-边-端协同可为大数据中心云服务器节约350%的存储容量,降低21.04%的能耗,验证了所提架构在实际工程中应用的有效性和合理性。

云南省国有林场管护用房建设现状分析与策略

云南省现有经国家林草局备案的国有林场142个,管护用房1166个,驻站人数5694人,共管护森林面积2770.58 m^(2),平均每个管护用房管护面积2.38万hm^(2),人均管护面积4866 hm^(2)。云南省国有林场管护用房建设采取了科学规划设计、精心组织实施、科学合理布局、项目和资金监管等做法,提升了国有林场的森林生态服务功能,进一步增强森林康养、森林旅游等优质生态产品的供给能力,有效促进林场林草产业发展。但目前尚存在建设布局不合理,基础设施不健全,现有建筑年久失修等问题。为此,提出加强规划设计和资金支持,提高管护人员待遇等策略。

大桂山林场桉树经营和高质量发展研究

桉树发展已经达到一定的规模,桉树高质量发展已引起社会广泛关注,然而国有林场的桉树如何高质量发展,仍报道甚少。本文从大桂山林场桉树经营的现状、存在问题两个维度进行研究,结合林场发展的实际情况,从良种选用,施肥管理等几个方面提出桉树经营和高质量发展的模式。以期对国有林场桉树高质量发展提供指导意义。

生态林场生态保护补偿机制探讨——以山东省东营市为例

生态林在提高森林覆盖率,调节生态功能,改善人居环境,满足人民群众生态需要等方面发挥着重要作用。推进生态林场建设对维护生态平衡,协调区域高质量发展和高水平保护具有现实意义。为了提升生态林场建设质量和保障生态林场的可持续发展,需要政府主导,各方参与,完善生态保护补偿政策和机制。以山东省东营市为例,结合座谈访谈、问卷调研、实地考察等方式进行梳理探讨,分析了立地条件相对较差地区生态林场生态保护补偿机制建设存在的问题,并对当前存在的问题提出对策建议,以期推动东营市生态林场的生态保护和可持续经营,为健全完善生态保护补偿机制提供参考依据。

国有林场森林资源管护优化策略研究——以樟木头林场为例

为增强樟木头林场的森林资源管护效果,本文首先分析了国有林场森林资源管护优化的必要性,并阐述了国有林场森林资源管理中存在的问题,基于具体问题,本文提出了有效的优化策略,实现了国有林场森林资源的可持续利用,以此为相关人员提供实践参考。

北京市十三陵林场管理处生物多样性分析与思考

该文通过2021年在十三陵林场管理处开展生物多样性调查,通过调查结果进行分析,结果表明:①野猪、岩松鼠和亚洲狗獾是十三陵林场管理处较为优势的兽类物种,整体生物多样性仍有较大提升空间;②鸟类物种丰富度在天然和恢复较好的混交林和阔叶林中较高;③建议减少人类的干扰,杜绝破坏野生动物栖息地的行为,从而打造良好的城市名片。

LNG储罐综合监控系统研发

当前国内储罐状态相关的监测系统与LNG储罐仪表测量系统相互独立设置、不兼容,各系统均独立运行,无法为安全生产运行及决策提供更加充分的依据,提出了将多套独立监控运行的软件集成为1套监控系统软件来实现对LNG储罐的精细化管理的相关技术。介绍了LNG储罐综合监控系统的总体设计,以及7个子系统功能,通过建立该综合监控系统不同子系统模型,将工艺条件变化后系统间相互的影响和变化直观展示,实现罐区异常状态下原因的快速分析和决策响应。

阿荣旗查巴奇林场森林资源现状与经营管理评价

文章以2022年阿荣旗查巴奇林场林草湿与第三次全国国土调查融合数据库为基础数据,对阿荣旗查巴奇林场森林资源状况及特点进行分析与评价,指出其存在的问题,提出应对措施,为今后林场可持续发展提供参考。

浅析贵州省国有扎佐林场多功能森林经营现状与对策

多功能森林经营能够生产最佳组合的产品和服务,满足公众的多样化需求,实现生态、经济和社会多重效益在相同的空间和时间上最大化。文章对贵州省国有扎佐林场多功能森林经营现状、存在问题及其原因进行剖析,结果表明:林场以针叶林和纯林为主,幼、中龄林比重较大,森林资源质量总体不高,森林旅游和康养活动仍有较大发展空间,森林多功能特色属性尚不明显。在此基础上,提出开展森林多功能经营区划、强化科技支撑、加强人员培训和转变经营理念等建议,以期为国有林场多功能森林经营管理提供参考。

国有林场森林经营类型制定研究——以长岛县国有长岛林场为例

该文以2019年度二类调查数据为基础,对长岛县国有长岛林场森林经营类型进行了研究。根据长岛森林所处的位置、生态条件、主导功能与分类经营的要求,进行森林经营类型组划分,并就两类森林经营类型组的功能定位、发展布局和经营技术措施进行了阐述。探索适宜海岛的森林经营方案,为海岛型国有林场改革后的森林经营提供示范。