Spatially explicit modeling of overstory manipulations in young forests: Effects on stand structure and light

Young forests can be manipulated in diverse ways to enhance their ecological values. We used stem maps from two dense, second-growth stands in western Washington and a spatially explicit light model (tRAYci) to simulate effects of five silvicultural manipulations on diameter distribution, species composition, spatial patterning, and light availability. Each treatment removed 30% of the basal area, but differed in how trees were selected for removal. Three primary treatments were thin from below (removing the smallest trees), random thin (removing trees randomly), and gap creation (removing all trees in circles ∼1 tree height in diameter). Two additional treatments combined elements of these approaches: random ecological thin (a mixture of thin from below and random thin) and structured ecological thin (a mixture of thin from below and gap creation).     

Neutral modelling of agricultural landscapes by tessellation methods—Application for gene flow simulation

Neutral landscape models are not frequently used in the agronomical domain, whereas they would be very useful for studying given agro-ecological or physical processes. Contrary to ecological neutral landscape models, agricultural models have to represent and manage geometrical patches and thus should rely on tessellation methods. We present a three steps approach that aimed at simulating such landscapes. Firstly, we characterized the geometry of three real field patterns; secondly, we generated simulated field patterns with two tessellation methods attempting to control the value of some of the observed characteristics and, thirdly, we evaluated the simulated field patterns. For this evaluation, we considered that good simulated field patterns should capture characteristics of real landscapes that are important for the targeted agro-ecological process. Real landscapes and landscapes simulated using either a Voronoi or a rectangular tessellation were thus compared when used as input data within a gene flow model. The results showed that neither tessellation method captured field shapes correctly, thus leading to over or (small) under estimation of gene flow. The Voronoi tessellation, though, performed better than the rectangular tessellation. Possible research directions are proposed to improve the simulated patterns, including the use of post-processing, the control of cell orientation or the implementation of other tessellation techniques.     

Monitoring and adaptive management: resolving social and organisational issues to improve information sharing in natural resource management

Adaptive, or 'learning by doing', approaches are often advocated as a means of providing increased understanding within natural resource management. However, a number of organisational and social issues need to be resolved if these approaches are to be used successfully. A case study in the South Island high country of New Zealand is used to review what is needed to support an ongoing community-based monitoring and adaptive management programme. First, the case study is described, paying attention to the social context of the resource management problem. The results of a workshop that explored this problem are then outlined, along with a proposed information flow suggested by participants. Requirements for future steps to resolve these problems (such as information protocols and a multi-stakeholder information system) are discussed. Finally, some broad lessons are drawn from this exercise that could help others developing similar approaches.     

Slope,aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland

The slope and aspect of a vegetated surface strongly affects the amount of solar radiation intercepted by that surface. Solar radiation is the dominant component of the surface energy balance and influences ecologically critical factors of microclimate, including near-surface temperatures, evaporative demand and soil moisture content. It also determines the exposure of vegetation to photosynthetically active and ultra-violet wavelengths. Spatial variation in slope and aspect is therefore a key determinant of vegetation pattern, species distribution and ecosystem processes in many environments. Slope and aspect angle may vary considerably over distances of a few metres, and fine-scale species’ distribution patterns frequently follow these topographic patterns. The availability of suitable microclimate at such scales may be critical for the response of species distributions to climatic change at much larger spatial scales. However, quantifying the relevant microclimatic gradients is not straightforward, as the potential variation in solar radiation flux under clear-sky conditions is modified by local and regional variations in cloud cover, and interacts with long-wave radiation exchange, local meteorology and surface characteristics.     

A Bayesian approach to multi-source forest area estimation

In efforts such as land use change monitoring, carbon budgeting, and forecasting ecological conditions and timber supply, there is increasing demand for regional and national data layers depicting forest cover. These data layers must permit small area estimates of forest area and, most importantly, provide associated error estimates. This paper presents a model-based approach for coupling mid-resolution satellite imagery with plot-based forest inventory data to produce estimates of probability of forest and associated error at the pixel-level. The proposed Bayesian hierarchical model provides access to each pixel’s posterior predictive distribution allowing for a highly flexible analysis of pixel and multi-pixel areas of interest. The paper presents a trial using multiple dates of Landsat imagery and USDA Forest Service Forest Inventory and Analysis plot data. The results describe the spatial dependence structure within the trial site, provide pixel and multi-pixel summaries of probability of forest land use, and explore discretization schemes of the posterior predictive distributions to forest and non-forest classes. Model prediction results of a holdout set analysis suggest the proposed model provides high classification accuracy, 88%, for the trial site.

Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Field monitoring of volatile organic compounds using passive air samplers in an industrial city in Japan

Highly portable, sensitive, and selective passive air samplers were used to investigate ambient volatile organic compound (VOC) levels at multiple sampling sites in an industrial city, Fuji, Japan. We determined the spatial distributions of 27 species of VOCs in three campaigns: Mar (cold season), May (warm season), and Nov (mild season) of 2004. In all campaigns, toluene (geometric mean concentration, 14.0microg/m3) was the most abundant VOC, followed by acetaldehyde (4.76microg/m3), and formaldehyde (2.58microg/m3). The spatial distributions for certain VOCs showed characteristic patterns: high concentrations of benzene and formaldehyde were typically found along major roads, whereas high concentrations of toluene and tetrachloroethylene (PCE) were usually found near factories. The spatial distribution of PCE observed was extremely consistent with the diffusion pattern calculated from Pollutant Release and Transfer Register data and meteorological data, indicated that passive air samplers are useful for determining the sources and distributions of ambient VOCs.     

Variation of MCPA, metribuzine, methyltriazine-amine and glyphosate degradation, sorption, mineralization and leaching in different soil horizons

Pesticide mineralization and sorption were determined in 75 soil samples from 15 individually drilled holes through the vadose zone along a 28 km long transect of the Danish outwash plain. Mineralization of the phenoxyacetic acid herbicide MCPA was high both in topsoils and in most subsoils, while metribuzine and methyltriazine-amine was always low. Organic matter and soil pH was shown to be responsible for sorption of MCPA and metribuzine in the topsoils. The sorption of methyltriazine-amine in topsoil was positively correlated with clay and negatively correlated with the pH of the soil. Sorption of glyphosate was tested also high in the subsoils. One-dimensional MACRO modeling of the concentration of MCPA, metribuzine and methyltriazine-amine at 2 m depth calculated that the average concentration of MCPA and methyltriazine-amine in the groundwater was below the administrative limit of 0.1 μg/l in all tested profiles while metribuzine always exceeded the 0.1 μg/l threshold value.     

博斯腾湖矿化度遥感反演及空间分布特征研究

以我国最大的内陆淡水湖——博斯腾湖为研究对象,利用Terra/MODIS L1B空间分辨率为250 m和500 m的遥感反射率数据及湖水矿化度实测数据建立线性回归模型,分析湖表面矿化度的空间分布特征。结果表明:空间分辨率为500 m的1~7个波段组合建立的多元线性回归模型相关性最高(R~2=0.70),模型验证结果显示,实测值和反演值的相关系数(R~2)为0.82,均方根误差(RMSE)为0.12。利用最优模型对博斯腾湖湖面矿化度进行反演,其分布存在明显的空间梯度,西北、东北和东南湖区矿化度较高,而西南湖区和湖区南部矿化度较低。     

既有住宅加装电梯重点问题分析与建议

目前全国既有住宅加装电梯工作还存在诸多问题,本文通过收集分析法规、文献资料、实地调研、交流研讨、召开专家咨询会等方式对既有住宅加装电梯工作在各个环节上存在的问题进行总结,并对加装电梯设计、地基、井道、应急救援、使用管理等方面提出安全要求建议,为监察管理、检验检测、安装使用等相关部门提供参考。