试论营林措施对森林病虫害防治的作用

采取营林措施开展病虫害防治工作,是从根本上防治病虫害的一种有效的方法和途径。本 文以病虫害防治中的营林措施为研究课题,通过探讨营林造林中的病虫害防治原则和防治措施以及 防治方法,探索该措施对于森林病虫害防治的作用和影响,旨在为促使和推动森林病虫害防治工作的 有效开展提供有益借鉴和参考帮助。     

Shading effects on canopy and tillering characteristics of continuously stocked palisadegrass in a silvopastoral system in the Amazon biome

In silvopastoral (SP) systems, forage responses depend on the microenvironment in which the plants develop. Our objective was to evaluate canopy and tillering characteristics of shaded 'Marandu' palisadegrass [Brachiaria brizantha (Hochst A Rich) Stapf, syn. Urochloa brizantha] under continuous stocking in a SP system. Treatments were one full sun (FS) and three shaded systems (silvopasture, SP) corresponding to distances from tree groves: 7.5 m north (SP1), and 15 m (SP2) and 7.5 m south (SP3) studied during two rainy seasons (Year 1 and Year 2). The tree in the SP system was Eucalyptus urograndis (hybrid of Eucalyptus grandis W. Hill ex Maiden × Eucalyptus urophylla S. T. Blake). The photosynthetic active radiation was greater in FS (923 μmol m^-2 s^-1), followed by SP2 (811 μmol m^-2 s^-1), SP1 (727 μmol m^-2 s^-1) and SP3 (673 μmol m^-2 s^-1). Forage accumulation in FS was 15% greater than the mean of SP1, SP2 and SP3 (10,663 kg DM/ha). There was no difference in net accumulation of leaf, stem and dead material, averaging 3,302, 3,420 and 4,063 kg DM/ha respectively. Leaf accumulation and accumulation rate were greater in Year 2, and leaf accumulation rate was similar among treatments (19 kg DM ha⁻¹ day⁻¹). Leaf proportion increased 14% from Year 1 to Year 2. Specific leaf area was greater for treatments SP1 and SP3 (193 cm²/g). Tiller population density was similar across treatments in Year 1. Shaded palisadegrass maintains leaf productivity similar to FS under continuous stocking in an SP system.     

云南松林下栽培滇黄精试验初报

[目的]探索云南松林下栽培滇黄精的技术。[方法]按照不同林分、坡位、密度设置样方,统计不同种苗类型、林龄类型、坡位类型、密度类型对林下栽培滇黄精生长的影响。[结果]在云南松林下栽培滇黄精,应选择块茎苗进行催芽处理,种植于排水较好的中坡位,郁闭度在0.6左右。[结论]为云南松林下栽培滇黄精提供了科学的依据。     

Exploring tree diversity and stand structure of savanna woodlands in southeastern Sudan

Savanna woodlands in Sudan host great biodiversity, provide a plethora of ecosystem goods and services to local communities, and sustain numerous ecological functions. Although the importance of the Acacia trees in these areas is well known, up-to-date information about these woodlands' diversity is limited and changes in their woody vegetation composition, density, diversity and relative frequency are not monitored over time. This study explored tree diversity and stand stage structure in Nuara Reserved Forest, a typical savanna woodland ecosystem in southeastern Sudan. A total of 638 circular sample plots (1000 m² for each) were established using a systematic sampling grid method. The distance between plots was 200 m. In each plot, all living trees with diameter at breast height (DBH) ≥5.00 cm were identified and counted, and their DBH values were recorded. From these data, tree composition, diversity, density and stage structure were assessed. There were 12,259 individual trees representing four species (Acacia seyal, Balanites aegyptiaca, Acacia Senegal and Acacia mellifera) that belong to two families. The dominant species was Acacia seyal. Average tree density was 191 trees/hm² and the Shannon-Weiner index for trees diversity was 0.204. Overall, young trees comprised 86.30% of the forest. The state of tree richness and density in the study area was low compared to other similar environments in the region and around the world. We recommended adoption of a proper management system that includes monitoring of woody vegetation diversity in this forest, and management actions to enhance tree diversity and sustain ecosystem services to local communities. In addition to care for the dominant Acacia seyal stands, more attention and conservation should be devoted to reestablishing Acacia senegal and Acacia mellifera trees because of their high ecological and economic values for local communities.     

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.     

基于农户视角的城郊区葡萄种植效益分析

基于陕西省西安市鄠邑区葡萄种植户的调查数据,在构建农户层面效益评价指标体系的基础上,评价了农户种植葡萄的效益状况。结果表明:第一,农户葡萄种植效益整体位于中等偏下的水平;第二,高效益农户与低效益农户在经济效益、生态效益以及就业机会上存在显著差异,而在对子女和老人的照顾上差异不大;第三,经验丰富、种植规模较大的纯农业型农户的效益较高。节水灌溉技术有助于提高农户的经济效益,而购买化肥的渠道、接受技术培训和有购买过假化肥经历对农户种植经济林的生态效益有影响。     

陕北黄土高原植被恢复对土壤理化性状的影响

为了解陕北黄土高原不同植被恢复类型对土壤理化性状的影响及其季节变化,采用完全随机设计,以陕北黄土高原恢复19年的杏树林、沙棘林、油松林和刺槐林为研究对象,以耕作相同年限农田为对照,分析不同植被恢复类型、土层和季节对土壤有机质、碱解氮、速效磷、速效钾、pH以及电导率的影响。结果表明,土壤有机质、速效磷和速效钾在不同人工林地间达到显著差异水平,人工林地土壤养分含量均高于玉米农地,杏树林和沙棘林相对较高,刺槐林相对较低。碱解氮、pH和电导率在不同人工林地间没有达到显著差异水平。随着土层加深,土壤有机质、碱解氮、速效磷和速效钾显著降低,pH和电导率土层间变化规律不一致。土壤有机质、碱解氮、速效钾和电导率在夏季和春季较高,土壤速效磷和pH在冬季和秋季较高。0~20 cm土层,有机质与碱解氮和速效钾均达到显著正相关水平;20~40 cm土层,土壤有机质与电导率呈显著正相关关系,速效磷与速效钾呈显著负相关;速效钾和电导率在各土层间均达到显著正相关水平,pH与电导率在各土层间均呈显著负相关关系。植被恢复显著提高了土壤养分,杏树林和沙棘林富集土壤养分能力优于油松林和刺槐林。     

三峡库区花岗岩母质石英砂土不同经济林模式土壤养分特征研究

为了解三峡库区花岗岩母质不同经济林模式的土壤养分状况,研究了各模式下土壤pH、有机质、全量养分和速效养分的特征,并利用主成分分析法对不同模式的土壤质量进行了综合评价。结果表明,除土壤pH外,经济林土壤有机质、全氮、全磷、全钾、碱解氮、有效磷、速效钾等含量的变异较宽,为中等变异。随土壤层次的增加,各模式下土壤有机质、全氮、速效氮、速效磷和速效钾含量呈递减趋势,而全磷和全钾则存在不规律变化。土壤有机质、全氮和速效钾对经济林土壤质量的高低产生着主要作用,土壤养分综合排名表现为柑橘（精细管理）>柑橘（常规管理）>板栗林>茶园。因此,利用生物措施和精细化管理措施,可有效提高该区域经济林的土壤质量。     

齐齐哈尔市城市森林空气负离子浓度变化规律

于2015-2017年的5-10月份,采取定位观测研究方法,在齐齐哈尔市城市森林中选取6个固定观测区,包括16种林分类型,在每个林分类型中设置固定观测点,进行逐月连年观测空气负离子浓度、正离子浓度以及空气温度湿度等环境因子,获取有效观测数据18万个;对观测数据系统全面分析,探索城市森林负离子浓度日变化、月变化、季节变化规律及时空分布格局。结果表明:经3 a连续观测,齐齐哈尔市城市森林空气负离子浓度的日变化规律,一般是早晨(06:00-08:00)达到峰值,随后下降,至中午或下午最低,晚上18:00左右再次出现峰值;负离子浓度最高值可达2000个/cm^3左右、最低值在300个/cm^3左右。齐齐哈尔市城市森林中,空气负离子浓度一年中的变化规律,从5月份开始逐月上升,到9月份达到峰值,从10月份开始下降,负离子浓度5月份最低,9月份最高。齐齐哈尔市城市森林各季节空气负离子浓度水平有所不同,秋季空气负离子浓度水平最高,夏季略低于秋季,春季最低。     

运用植被指数时序特征对落叶松人工林分类

为探究植被指数时序特征是否有利于落叶松人工林提取,以孟家岗林场为研究试验区域,根据落叶松人工林季相和物候特征,利用Landsat8OLI影像数据提取研究区内5种植被的归一化植被指数(I NDV)、差值植被指数(I DV)、比值植被指数(I RV)、增强型植被指数(I EV),构建相应的植被指数时序特征。采用最大似然和随机森林两种方法对单一时相影像和加入植被指数时序特征的影像进行对比试验。结果表明:影像中加入植被指数时序特征后,最大似然算法的分类总体精度为89.53%,Kappa系数为0.87,比单一时序特征的影像分类精度提高了13.35%;随机森林算法的森林类型分类总体精度为93.22%,Kappa系数为0.92,比单一时序特征的影像分类精度提高了19.8%。因此,加入植被指数时序特征后能得到更高的落叶松人工林提取精度。