护林防火技术在森林资源保护中的应用

合理运用护林防火技术可以提升森林资源保护工作的整体质量,推动林业不断发展。本文分析了森林火灾发生的原因,总结了护林防火技术,提出了相关应用对策,以期为减少森林火灾的发生和保护森林资源提供参考。     

龙竹高产栽培技术

龙竹为大型丛生竹，具有重要的经济价值和生态价值。文章试验研究了育苗方式、坡向、肥料种类以及造林整地方式对龙竹生长的影响。结果表明：与其他育苗方式相比，龙竹组培苗造林竹株生长好，竹材产量高；龙竹适宜栽植于阴坡，采用全面整地法，在造林后的前4年每年施用适量的氮磷钾复合肥，可培育出高产的龙竹林。     

上海半自然森林更新苗物种组成与多样性研究

城市半自然森林具有独特的群落结构和生物多样性特征,研究城市化影响的半自然森林更新特征,可以为城市生物多样性保育与地带性植被恢复重建提供借鉴。文章以上海辰山残存半自然森林1 hm^2固定监测样地为对象,调查分析半自然森林更新苗的物种组成特征。结果表明:1 hm^2样地更新苗共5 937株,分属22科32属37种,其中上海自然分布的乡土种占57.89%,明显高于城市人工林的乡土树种比例;香樟、构树、天竺桂、朴树和小蜡等5种更新苗占总数的57.2%,聚集性分布格局明显;在11个植被群落类型中,各类型更新苗的丰富度普遍较高,不同树种的更新苗存活和发育潜力存在差异。     

内蒙古大兴安岭北部原始林区森林火灾应急资源储备与调度研究

【目的】为更好地开展原始林区森林灭火工作,保护内蒙古大兴安岭北部原始林区森林生态资源。【方法】对内蒙古大兴安岭重点国有林管理局下辖的22个林业局,3个自然保护区的应急资源储备情况进行了整理,同时对北部原始林区森林火灾发生的时间规律和空间规律分别进行了分析,在此基础上采用ArcGIS软件,对内蒙古大兴安岭重点国有林管理局森林火灾应急资源的空间分布状况与内蒙古大兴安岭北部原始林区近5年森林火灾发生的空间分布状况进行了叠加分析,依据叠加分析的结果对内蒙古大兴安岭重点国有林管理局森林火灾应急资源空间分布的合理性进行了评判。【结果】叠加分析结果显示,目前内蒙古大兴安岭北部原始林区周边林业局森林火灾应急资源空间配置存在区域集聚以及北部原始林区附近应急资源配置不足等不合理问题。在对内蒙古大兴安岭重点国有林管理局森林火灾应急资源储备情况整理分析的基础上,创新性地提出了以应急物流系统所需时间最少和费用最小为目标进行优化的森林火灾应急资源分配模型。【结论】最后通过实例证明,该模型可以优化森林火灾应急物流系统中资源配置体系,为应急资源的合理调配提供了指导,对于实现科学决策指挥,保护北部原始林区森林生态资源具有一定的现实意义。     

基于距离相关系数和KNN回归模型的森林蓄积量估测研究

【目的】探究Landsat8 OLI数据和KNN算法在森林蓄积量估测中的潜力。【方法】以湖南省湘潭县为研究区,采用Landsat8 OLI数据和同时期的二类调查数据,通过距离相关系数筛选特征,分别采用线性回归模型(MLR)、K-近邻模型(KNN)、距离加权KNN模型(DW-KNN)和优化欧式KNN模型(FW-KNN)对森林蓄积量进行估测。使用十折交叉方法进行精度检验,对检验结果进行对比分析。【结果】3种KNN模型的估测结果均高于传统的线性模型,并且在3种KNN模型中,FW-KNN算法效果最好,决定系数达到0.69,为3种模型中最高;3种KNN模型中,本研究优化欧氏距离KNN模型的估测精度最高,其均方根误差为30.3%,相比于传统KNN模型的均方根误差降低了5.1%,相比于DW-KNN模型降低了3.3%。【结论】采用DW-KNN蓄积量估测结果明显优于其他两种模型,说明通过特征与蓄积量的相关性优化样本间的距离是一种可行的KNN优化方法。     

黔东南州打造全域森林公园的可行性研究

指出了建设全域森林公园是经济和社会发展的必然要求。在对黔东南州发展全域森林公园进行必要性和打造条件后认为:黔东南州在打造全域森林公园方面具有明显的政策优势,有着优良的森林生态环境资源,以及良好的林业产业基础等优势条件。通过不断完善相关的配套服务体系,已具备了打造全域森林公园的可行性。     

Distribution and diversity of leaf-cutting ants in Northeastern Argentina: species most associated with forest plantations

Abstract

Leaf-cutting ants (LCA) are considered one of the main herbivores and one of the most destructive pest insects of the Neotropics. Northeastern Argentina harbors the greatest species richness of these ants and in turn comprises the highest surface with forest plantations. Our aim was to establish which species of leaf-cutting ants are most commonly associated with forest plantations by analyzing their geographic distribution using published and unpublished species occurrence data. Also, estimate their potential areas of distribution along a latitudinal gradient that entirely encompasses northeastern Argentina using Ecological Niche Modeling. Only seven of the 20 species recorded were strongly associated with productive systems along the gradient, but only 2–3 species in each region could be considered high-risk species for forest plantations. High-risk species composition shows a turnover between regions. Our models show the potential distribution areas where LCA could become more abundant and dominant, and possibly causing a detrimental effect on the forest plantations in the studied region. We find that ecological niche models are useful tools to assess the environmental suitability of important LCA.     

粤北地区食用菌产业及其循环经济发展概述

从食用菌种类及其分布、产值、食用菌企业、食用菌产业循环经济发展情况等方面介绍了粤北地区食用菌产业发展现状,总结食用菌产业发展中存在的问题,如菌种问题突出,品牌意识缺乏;食用菌产业标准化落后;产品质量参差不齐,食品质量安全无保障;资源浪费严重;精深加工不足等,并提出相应的对策。     

森林康养步道五感体验需求与潜在游客体验意愿分析

【目的/意义】通过探索五感体验需求对潜在游客体验意愿的驱动影响,以期能够准确理解与把握潜在游客的行为意向,为森林康养步道设计提供理论参考。【方法/过程】以潜在游客为研究对象,借助AMOS构建结构方程模型,并引入“认知程度”这一调节变量进行层级回归分析。【结果/结论】结果表明:五感体验需求对潜在游客选择体验森林康养步道的意愿具有正向显著影响;在森林康养步道中,对五感体验需求影响最大的为触觉体验需求,其次为嗅觉体验需求、视觉体验需求和听觉体验需求,影响最小的是味觉体验需求;潜在游客对森林康养的认知程度对于五感体验需求与体验意愿之间的关系具有正向调节作用。     

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.