Roads and Landscape Pattern in Northern Wisconsin Based on a Comparison of Four Road Data Sources

Abstract:  Roads are important components of landscapes; they fragment habitat, facilitate invasive species spread, alter hydrology, and influence patterns of land use. Previous research on the ecological impacts of roads may have underestimated their effect because currently available sources of road data do not include the full road network. We compared differences in road density and landscape pattern among U.S. Census Bureau TIGER line files, U.S. Geological Survey 1:100,000-scale digital line graphs, and U.S. Geological Survey 1:24,000-scale digital raster graphics in northern Wisconsin to road data derived from 1:40,000-scale digital orthophotos. Road density measured from digital orthophotos (2.82 km/km²) was significantly greater than that of digital raster graphics (1.62 km/km²) and more than double that of digital line graphs (1.21 km/km²) and TIGER (1.27 km/km²) data. The increased road densities in raster graphics and orthophoto data were mainly due to the addition of minor roads. When all roads were used to define patch boundaries, landscape metrics produced with orthophoto data showed significantly greater levels of fragmentation than those based on line or raster graphics. For example, maximum patch size was 1074 ha and total edge was 109 km for line graphs, compared with 686 ha and 211 km for orthophoto data. Roads are missing in commonly used data, primarily because mapping standards systematically exclude minor roads. These standards are not ecologically based and may result in false assumptions about the ecological effects of roads. We recommend that future studies take special consideration of the completeness of road data and consider whether all ecologically relevant roads are included.     

Copper distribution in chemical soil fractions and relationships with maize crop yield

Agricultural practices can lead to copper accumulation in soils and at high concentration it can become toxic for plants. One common toxic effect of copper on plants is a decrease of crop yield. Here, we studied 1) the crop yield of maize grown on plots of a soil intentionally enriched with copper sulphate and 2) the possible relationship between the copper concentration in chemical soil fractions and the maize crop yield. Anthropogenic copper is mainly bound to manganese oxides, to iron oxides and to the organic matter. Maize (Zea maize L.) was grown on outdoor experimental plots. The crop yield was evaluated for three development stages: the 6–10 leaf stage, the female flowering stage and the maturity stage, 2, 4 and 6 years after the soil copper enrichment. Strong crop yield reductions, proving a toxic effect of copper on maize growth were noted 2 years after the copper input at the maturity stage and 4 years after the copper input at the 6–10 leaf stage. Variations in maize crop yield are described with linear multiple regression equations including the variable copper content in soil, and other variables when needed such as soil pH, soil organic carbon level and the climatic variables, the precipitation rate and the ambient temperature. The crop yield study at the 6–10 leaf stage and at the female flowering stage does not provide significant regression equations, while the crop yield study at the maturity stage does. Request variables for the models are the total copper content or the copper bound to the organic matter and the meteorological data. Electronic Publication     

Soil Lead and Children’s Blood Lead Levels in Syracuse, NY, USA

A geo-referenced data set of 12 228 first-time blood lead screening values for Syracuse, NY, children was established for the 4-year period 1992–1996. Soil lead values were measured in a 600 m by 600 m tessellation grid covering the city. The two data sets were merged for evaluation of relationships between them. Strong seasonal variation in blood lead levels suggests the importance of contaminated soils as an exposure source. When the data were aggregated at a large geographic scale (3 km²), a logarithmic model showed an R² of > 0.65 for the regression of geometric mean blood lead on median soil lead values. Results showed a striking similarity to those obtained by Mielke et al. (1999) for a study in New Orleans, LA, USA.     

Extinction Rate Estimates for Plant Populations in Revisitation Studies: Importance of Detectability

Abstract:  Many researchers have obtained extinction-rate estimates for plant populations by comparing historical and current records of occurrence. A population that is no longer found is assumed to have gone extinct. Extinction can then be related to characteristics of these populations, such as habitat type, size, or species, to test ideas about what factors may affect extinction. Such studies neglect the fact that a population may be overlooked, however, which may bias estimates of extinction rates upward. In addition, if populations are unequally detectable across groups to be compared, such as habitat type or population size, comparisons become distorted to an unknown degree. To illustrate the problem, I simulated two data sets, assuming a constant extinction rate, in which populations occurred in different habitats or habitats of different size and these factors affected their detectability. The conventional analysis implicitly assumed that detectability equalled 1 and used logistic regression to estimate extinction rates. It wrongly identified habitat and population size as factors affecting extinction risk. In contrast, with capture-recapture methods, unbiased estimates of extinction rates were recovered. I argue that capture-recapture methods should be considered more often in estimations of demographic parameters in plant populations and communities.     

Climatic Change, Wildfire, and Conservation

Abstract:  Climatic variability is a dominant factor affecting large wildfires in the western United States, an observation supported by palaeoecological data on charcoal in lake sediments and reconstructions from fire-scarred trees. Although current fire management focuses on fuel reductions to bring fuel loadings back to their historical ranges, at the regional scale extreme fire weather is still the dominant influence on area burned and fire severity. Current forecasting tools are limited to short-term predictions of fire weather, but increased understanding of large-scale oceanic and atmospheric patterns in the Pacific Ocean (e.g., El Niño Southern Oscillation, Pacific Decadal Oscillation) may improve our ability to predict climatic variability at seasonal to annual leads. Associations between these quasi-periodic patterns and fire occurrence, though evident in some regions, have been difficult to establish in others. Increased temperature in the future will likely extend fire seasons throughout the western United States, with more fires occurring earlier and later than is currently typical, and will increase the total area burned in some regions. If climatic change increases the amplitude and duration of extreme fire weather, we can expect significant changes in the distribution and abundance of dominant plant species in some ecosystems, which would thus affect habitat of some sensitive plant and animal species. Some species that are sensitive to fire may decline, whereas the distribution and abundance of species favored by fire may be enhanced. The effects of climatic change will partially depend on the extent to which resource management modifies vegetation structure and fuels.     

NONLINEAR MODELING AND PREDICTION OF A RIVER FLOW SYSTEM1

ABSTRACT: Model estimation and prediction of a river flow system are investigated using nonlinear system identification techniques. We demonstrate how the dynamics of the system, rainfall, and river flow can be modeled using NARMAX (Nonlinear Autoregressive Moving Average with eXogenuous input) models. The parameters of the model are estimated using an orthogonal least squares algorithm with intelligent structure detection. The identification of the nonlinear model is described to represent the relationship between local rainfall and river flow at Enoree station (inputs) and river flow at Whitmire (output) for a river flow system in South Carolina.     

Exchange of sulfur pollution between Bulgaria and Greece

The EMAP model (Eulerian Model for Air Pollution) is applied for calculating the sulfur concentration and deposition fields for 1995 as based upon Bulgarian and Greek sources. The country-to-country budgets show that about 4% of the sulfur oxides emitted by Bulgaria are deposited over Greek territory, estimated at 28 kt S. Only 2% of sulfur compounds emitted by Greece are deposited over Bulgaria, estimated at 6.2 kt S for 1995. This data is in agreement with EMEP/MSC-W estimates and provides more details concerning time and space. The results can be used in decision-making, negotiating and the development of contamination strategies.     

沈阳市垃圾填埋处理甲烷产量研究

分析了4种典型的生活垃圾填埋处理甲烷产气量模型：IPCC模型、化学计量式模型、COD模型和生物降解理论模型;利用这4种模型估算沈阳市生活垃圾的甲烷产气总量,对计算结果的差异进行比较讨论;分析了4种模型的优缺点及其不同的适用性;根据沈阳市城市生活垃圾的特点,建议采用生物降解理论模型来估算沈阳市垃圾填埋甲烷产气量。     

典型环境条件下装备环境适应性的评估方法

系统分析了航空装备环境适应的特点及环境适应性要求的类型。在此基础上,根据装备的相关环境试验信息和外场环境故障信息,遵循确定模糊集隶属函数的原则,分别构建了描述装备对单因素环境适应性的隶属度。基于单因素评估结果,选择合适的确定权重的方法,确定模糊综合评判中各层次因素的权重。最后选择合适的合成算子采用模糊综合评估的方法分别提出了装备与下层产品的综合环境适应性评估方法。通过实例验证了模型的合理性和方法的可行性。