Using digital image projections to visualize forest landscape changes due to management activities and forest growth

A pedagogic problem in forestry and landscape management is to visualize future landscape effects of forest growth and current management activities in the forest. This paper presents a method for forecasting digital image projections of forest landscape dynamics. Static nonlinear regression functions estimate the digital numbers in a Landsat Thematic Mapper image. Regressors used are forest stand variables. By estimating the future forest stand data, based on intermediate treatment and growth, future satellite digital images are created. In a case study example, the future landscape of a forest block in the province of Västernorrland, Sweden, is projected to demonstrate the application of this visualization technique.     

Resource Use Dynamics and Land-Cover Change in Ang Nhai Village and Phou Phanang National Reserve Forest, Lao PDR

This study integrated aerial photographs from 1952, 1981, and 1998, and a satellite image from 2000 with oral histories and socioeconomic surveys to assess changes in forest and land cover in Ang Nhai village, Laos. The study documents the history of resource use and changes in household access to resources in the village. Three distinctive trends were observed in terms of forest and land cover—forest degradation, deforestation, and regeneration. Project results suggest that land and forest cover change dynamically under different circumstances. The case study also points out that integration into the market economy can induce intensification of unused lowland areas, while removing pressures from upland areas previously used for supplementing agricultural production. In addition, the creation of a national reserve forest to restrict local access and forest use was an ineffective tool for regulating encroachment and logging activities.     

基于机器学习分类算法解析EIS数据的有机涂层性能评价方法

目的 基于机器学习分类算法快速评估有机涂层的防腐性能。方法 通过实验室加速试验模拟涂层真实的退化过程,并根据测得的电化学数据,分析不同退化阶段的等效电路元件参数。随后,采用随机抽样方法获取大量数据,用于机器学习模型训练。通过对比支持向量机(SVM)、k最近邻(k-NN)和随机森林(RF)3种不同的机器学习算法,以及多种输入特征集训练的涂层性能分类器模型的准确率,分析最适合用于涂层性能快速评估的机器学习算法和电化学特征。结果 根据不同输入特征训练的k-NN和RF模型均表现出良好的预测效果,而SVM模型的预测效果相对较差。根据不同频率范围训练的分类器模型中,在低频区表现最佳,而在高频区表现较差。结论 基于阻抗虚部、虚部+实部和阻抗模值3种输入特征训练的RF分类器模型的预测效果最准确。不同频率区间内,低频区的阻抗特征更能准确表征涂层性能。     

Amounts of pesticides reaching target pests: Environmental impacts and ethics

Less than 0.1% of pesticides applied for pest control reach their target pests. Thus, more than 99.9% of pesticides used move into the environment where they adversely affect public health and beneficial biota, and contaminate soil, water, and the atmosphere of the ecosystem. Improved pesticide application technologies can improve pesticide use efficiency and protect public health and the environment.     

旅游踩踏对土壤微生物生物量碳、氮、磷的影响

为了探明旅游活动对张家界国家森林公园土壤微生物活性及多样性的影响,保护土壤生态平衡及合理开发自然保护区提供理论依据,进行了旅游踩踏对土壤微生物生物量碳、氮、磷的影响研究.结果表明,在所设的3个试验区中,0～5cm土壤层的微生物生物量碳、磷受到旅游踩踏的影响最严重,5～15cm土壤层的微生物生物量碳、磷受到旅游踩踏的影响较严重,而15～25cm土壤层的微生物生物量碳、磷受到旅游踩踏的影响最轻,旅游踩踏对所设3个试验区中3个层次土壤的微生物生物量碳、磷的影响均达到了显著水平(p＜0.05).从旅游踩踏对3个土壤层的微生物生物量氮的影响程度来看,0～5cm土壤层的微生物生物量氮受到的影响最严重,5～15cm土壤层的微生物生物量氮受到的影响较严重,而15～25cm土壤层的微生物生物量氮受到的影响最轻,背景区与缓冲区15～25cm土壤层的微生物生物量氮差异没有达到显著水平.说明张家界国家森林公园土壤微生物遭到了旅游踩踏的破坏,抵御外界干扰的能力已受到了旅游踩踏的破坏.     

Impact of bias in predicted height on tree volume estimation: A case-study of intrinsic nonlinearity

Bias originating from intrinsic nonlinearity in nonlinear models is caused by excess curvature in the solution locus of parameter estimates derived from least squares procedures. Bias due to intrinsic nonlinearity varies according to sample size as well as model specification. This paper analyses consequences of fractionising data into smaller sub-samples. Based on measurements of stem diameter and total tree height from the first Danish national forest inventory, it is demonstrated how data splitting at random may cause the intrinsic nonlinear curvature to exceed the critical F-value. Application of a Taylor-series expansion shows that, for all practical purposes, the bias in predictions of individual tree volume (based on stem diameter and tree height) is negligible. To minimize residual variance, intrinsic curvature and, in turn, prediction bias, it is recommended that data be stratified according to site conditions, stand characteristics or other relevant criteria. Finally, the preferred model should exhibit close-to-linear behaviour.     

Balancing Conservation and Economic Sustainability: The Future of the Amazon Timber Industry

Logging has been a much maligned feature of frontier development in the Amazon. Most discussions ignore the fact that logging can be part of a renewable, environmentally benign, and broadly equitable economic activity in these remote places. We estimate there to be some 4.5 ± 1.35 billion m³ of commercial timber volume in the Brazilian Amazon today, of which 1.2 billion m³ is currently profitable to harvest, with a total potential stumpage value of $15.4 billion. A successful forest sector in the Brazilian Amazon will integrate timber harvesting on private lands and on unprotected and unsettled government lands with timber concessions on public lands. If a legal, productive, timber industry can be established outside of protected areas, it will deliver environmental benefits in synergy with those provided by the region’s network of protected areas, the latter of which we estimate to have an opportunity cost from lost timber revenues of $2.3 billion over 30 years. Indeed, on all land accessible to harvesting, the timber industry could produce an average of more than 16 million m³ per year over a 30-year harvest cycle—entirely outside of current protected areas—providing $4.8 billion in returns to landowners and generating $1.8 billion in sawnwood sales tax revenue. This level of harvest could be profitably complemented with an additional 10% from logging concessions on National Forests. This advance, however, should be realized only through widespread adoption of reduced impact logging techniques.     

Mitigation and adaptation synergy in forest sector

Mitigation and adaptation are the two main strategies to address climate change. Mitigation and adaptation have been considered separately in the global negotiations as well as literature. There is a realization on the need to explore and promote synergy between mitigation and adaptation while addressing climate change. In this paper, an attempt is made to explore the synergy between mitigation and adaptation by considering forest sector, which on the one hand is projected to be adversely impacted under the projected climate change scenarios and on the other provide opportunities to mitigate climate change. Thus, the potential and need for incorporating adaptation strategies and practices in mitigation projects is presented with a few examples. Firstly, there is a need to ensure that mitigation programs or projects do not increase the vulnerability of forest ecosystems and plantations. Secondly, several adaptation practices could be incorporated into mitigation projects to reduce vulnerability. Further, many of the mitigation projects indeed reduce vulnerability and promote adaptation, for example; forest and biodiversity conservation, protected area management and sustainable forestry. Also, many adaptation options such as urban forestry, soil and water conservation and drought resistant varieties also contribute to mitigation of climate change. Thus, there is need for research and field demonstration of synergy between mitigation and adaptation, so that the cost of addressing climate change impacts can be reduced and co-benefits increased.     

兴文石林地质地貌景观的脆弱化趋势研究

兴文石林是喀斯特岩溶地质风景名胜区兴文石海的中心景区,喀斯特岩溶山地的生态环境具有一定脆弱特性,随着旅游业的不断发展,景区加大了开发力度,可能导致景区脆弱性的加剧,为了保证在旅游开发中能对景区重要的地质资源进行更好地保护,采用生态脆弱区评级指标及权重值评分法对兴文石林的10个主景点进行了研究,分析得出,兴文石林存在轻生态脆弱性、中生态脆弱性和强生态脆弱性三种梯度趋向,其中,脆弱性最强区域面积达到2平方公里的面积,这些区域分布在景区的边缘地带,因此,要实现旅游资源的可持续利用,必须对强生态脆弱性区域实行禁游和实行退耕还林等措施,以防止脆弱区域的扩大和脆弱性加剧.