The re-emergence of indigenous forest in an urban environment, Christchurch, New Zealand

Christchurch, the second largest city in New Zealand is a planned city on a coastal plain on the east coast of the South Island. The birth of the city and the subsequent century of development was characterised by colonial values and tree and garden planting with familiar European species along with those from Australia, North America, and eventually all other continents. The image of an “English garden city” with classical parks of oaks and willow-lined rivers became the accepted norm and the way in which the city has been promoted to potential tourists. Gardening is one of the top two recreational activities and exotic species greatly outnumber native species in the flora and in gardens. This has had serious consequences for the highly fragmented and degraded indigenous vegetation and its co-adapted wildlife. A few hardy indigenous species continued to regenerate through this period, but since the 1970s, there has been a progressive change of attitude and interest in reclaiming the natural heritage of the city, manifest in widespread private and public planting of indigenous species and active habitat restoration. In this article we examine the indigenous and exotic shrub and tree components of the Christchurch flora as planted street trees, in domestic gardens, and in parks. We also present data on shrub and tree regeneration in parks and domestic gardens in the city. Indications are that the more sensitive, less intrusive management of urban environments, combined with the greater density of indigenous seed sources, has allowed regeneration of a wide range of indigenous species across a broad spectrum of habitats – from neglected gardens to pavement cracks to exotic plantations. This is despite the competition from the prodigious seed banks and density of exotic trees, shrubs, and ground covers and albeit minimal impacts of introduced browsing and seed eating mammals. If the present trends continue through appropriate management and facilitation, these tentative signs of native forest regeneration should eventually proliferate into a sustainable mixed origin urban forest that resurrects and preserves the natural character of the region.     

朝阳市主要经济林树种经济效益评价及发展预测

以朝阳地区主要经济林树种1958~2005年资料为基础,对山杏、大扁杏和大枣的经济效益进行科学评价。并采用数理统计方法,对3种主要经济林树种未来10年的发展前景进行了预测。     

云和县生态公益林的发展现状与管理对策

对云和县生态公益林的资源和发展现状进行了调查分析,提出了今后云和县生态公益林的发展对策,以实现生态公益林的持续、稳定和健康发展。     

江西铜鼓县公益林效益计量评价

通过等效益转换和货币置换,将森林多种效益币值化。计算出铜鼓县公益林总效益为58 150.17万元(1999年现价)。其中,生态效益、社会效益、有形产品三者的经济价值分别为30 840.11万元、20 401.28万元、6 908.78万元。除掉生态效益中净化大气这一潜在价值,得出三者经济价值比为1.83∶1∶。     

退耕还林还草地鼠类调查及控制对策研究

2002-2003年对青海省大通县退耕还林还草地鼠类组成进行调查研究,捕获鼠类6种728只,以根田鼠Microtus oeconomus和高原鼢鼠Myospalax baileyi为绝对优势种.4种方法进行退耕还林还草地害鼠控制的结果表明:人工置夹和药物控制是地上害鼠控制的有效方法,人工地箭与灭鼠雷可有效控制地下高原鼢鼠的数量.但从长远来看,控制退耕还林还草地鼠害应采取生态治理的原则和方法.     

小兴安岭天然林不同树种的树高曲线模型

选用10种树高曲线模型作为候选模型,以决定系数(R~2)、残差平方和(S_(se))和均方差(M_(se))作为模型优劣的评价指标,对小兴安岭天然林中的云杉(Picea asperata)、红松(Pinus koraiensis)、水曲柳(Fraxinus mandschurica)、椴树(Tilia tuan)4种树种的树高曲线模型进行优选。结果表明:云杉、红松和椴树的最优模型均为Logistic模型,水曲柳的最优模型为抛物线模型;云杉和红松两种针叶树种,最优模型的优势不明显,水曲柳和椴树两种阔叶树种最优模型的优势较明显;比较R~2的大小,得出较适合小兴安岭云杉和红松两种针叶树种的树高曲线模型(R~20.8),对小兴安岭阔叶树种的适用程度不具有普遍性,对椴树的适用性好(R~2最大达0.94),对水曲柳的适用性较差(R~20.8)。对水曲柳的树高进行分段研究得出:水曲柳在树高低于9 m时,树高曲线模型较适宜(R~20.8),其中抛物线模型为最优模型;树高较高时,没有适用的树高曲线模型。     

广西5种人工林地土壤微生物数量及土壤酶活性分析

为当地珍贵速生树种人工林的发展及合理利用提供理论依据。分析广西5种珍贵树种人工林土壤微生物数量及土壤酶活性差异,以相同立地条件下12年生的黑木相思(Acacia melanoxylon)、老排(Mytilaria laosensis)、红椎(Castanopsis hystrix)、黧蒴椎(Castanopsis fissa)和火力楠(Michelia macelurei)人工纯林为研究对象,采用稀释平板涂布法和土壤酶活性测定法,测定和分析该5种人工林地土壤微生物数量及酶活性。结果表明:5种林地的土壤微生物总数和细菌数量大小均为:火力楠黧蒴锥红椎黑木相思米老排。但5种林地的土壤酶活性大小不一,蔗糖酶、脲酶、蛋白酶、酸性磷酸酶活性在5种林地之间的差异极其显著,而过氧化氢酶活性不显著。5种林地中土壤酶活性相对较强的是米老排人工林,较弱的是黑木相思林和火力楠林。土壤酶活性与微生物数量的相关分析表明,土壤中蔗糖酶活性与放线菌数量呈极显著正相关关系,其余相关性没有达到显著水平。     

舒城县油茶低产林类型与综合改造技术模式

舒城县是安徽省油茶重点发展县,油茶产业开发走在全省的前列。本文阐述了舒城县现有油茶低产林类型、改造模式及其技术措施,对分类实施油茶低改具有一定现实意义和指导意义。     

天然杨桦用材林高效经营技术研究

选择不同林分类型和立地条件,按不同经营密度分别设立固定标准地,开展立地类型划分和最适密度选择。同时,在固定标准地内,对林分生长性状、形质指标、干物质积累量、枯枝落叶分解量及养分归还量进行连续定位观测。结果表明:经营密度对林分生长、干物质积累和枯枝落叶分解影响较大,且以中等经营密度(0.7)效果最理想。在立地类型划分、最适经营密度选择、密度效应分析、径级-株数分布规律研究的基础上,针对不同培育目标,分别提出不同立地条件下天然杨桦(胶合板材、普通建筑材、纸浆材)用材林高效经营技术,为科学经营存量种质资源,最大限度提高森林生产力奠定理论基础。     

Prediction of pine mistletoe infection using remote sensing imaging: A comparison of the artificial neural network model and logistic regression model

In this study, the prediction of pine mistletoe distribution in Scots pine ecosystems was explored using remote sensing variables to compare the multilayer perceptron (MLP) artificial neural network (ANN) and logistic regression (LR) model performances. For this purpose, 109 sample plots were distinguished in pure Scots pine forests (natural) in the Eastern Black Sea Region of Turkey. Distinguishing mistletoe-infected stands (69) and uninfected stands (40) was performed with field observations. The variables acquired from Landsat 8 (Level 1) images were used as independent variables for independent-sample t-test, MLP ANN and LR models. Remote sensing variables indicated that mistletoe-infected stands were in drier areas with a lower vegetation-leaf area index. Based on the performance results of both models, the sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV) and accuracy of the MLP ANN model were superior to those of the LR model. The prediction percentages (SEN, SPE, PPV and NPV) of mistletoe-infected stands were better than the prediction percentages of uninfected stands. The prediction accuracies of LR and MLP ANN models were 74.3% and 89.6%, respectively. However, all remote sensing variables were included in the prediction equation of the MLP ANN model, while the thermal infrared 1 (TIRS1) variable was included in the LR model. In the MLP ANN model, the TIRS1 variable also had the highest normalized importance (100%). The area under the curve (AUC) value for identifying the mistletoe-infected stands of Scots pine forests used by the MLP ANN model (0.892 ± 0.034) was higher than in the LR model (0.838 ± 0.039), explaining the more accurate predictions obtained from the MLP ANN model. The MLP ANN model showed much better performance than the LR model. The results of this study are expected to make important contributions to the identification of potential mistletoe-infected areas.