Deforestation in the drylands of Africa: Quantitative modelling approach

This paper has developed a two-sector model of forestry that gives some insights into the interactions of poverty, land tenure insecurity, economic growth, trade and deforestation in the context of the drylands of Africa. Externally, the model results show that the world demand for non-timber forestry products can lead to a win-win situation whereby both trade and environmental sustainability can be promoted. Monopolistic measures to control the supply of these products, for short-term price gains, are harmful economically and environmentally. By contrast, productivity-raising measures have a favourable impact on both the economy and the environment. Internally, the model results show that the growth of the rest of the economy has driven the economic growth of the forestry sector, but at the same time, its environmental degradation. Poverty and land tenure insecurity also contribute to this degradation. Fortunately, policies promoting basic needs satisfaction and property rights security are shown to be effective in mitigating environmental degradation in the forestry sector. The paper results contribute towards a more sustainable exploitation of forestry.Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue.     

中国西部地区生态扶贫策略研究

西部地区是我国贫困面最大、贫困程度最深的地区,同时也是生态环境最脆弱的地区.改革开放以来,虽然西部地区社会经济发展水平得到了一定的提高,但与东中部地区的收入差距却在不断的扩大.同时,随着全国贫困人口绝对规模的减少,贫困人口的分布进一步向西部地区集中,生态环境在诸多致贫因素中越来越突出.文章从西部贫困地区与生态脆弱区和重要生态功能区空间分布的关联性以及地区贫困对生态环境的影响等方面深入解析了西部地区贫困和生态环境互为因果的耦合机理;分析了当前西部地区扶贫开发面临的生态环境、资金、人力资本、管理体制等方面的严峻挑战;提出了生态扶贫的概念和基本内涵,即:生态建设与扶贫开发同步进行,生态恢复与脱贫致富相互协调;设计了原地扶贫和离地扶贫两大生态扶贫模式,并提出了不同生态扶贫模式的特点、实施范围和基本内容.原地扶贫通过创造生态管护就业岗位,发展当地特色生态绿色产业体系,实现贫困人口在当地就业,增加贫困人口的收入.同时,通过拓展整村推进和本地教育工程,改善贫困地区生产、生活条件,提高贫困人口稳定脱贫能力.离地扶贫则以生态移民为主,并结合城镇化战略,引导贫困地区劳动力向城镇和东部沿海地区转移,通过异地就业、生活实现脱贫.最后,提出了实施生态扶贫战略的相关政策建议,包括以教育为核心的人力资本开发,以特色农副产品开发、特色生态旅游和绿色品牌建设为核心的特色优势产业发展,以及以生态移民制度和政府管理体制为核心的制度建设创新等.     

A study of the atmospheric dispersion of a high release of krypton-85 above a complex coastal terrain, comparison with the predictions of Gaussian models (Briggs, Doury, ADMS4)

Atmospheric releases of krypton-85, from the nuclear fuel reprocessing plant at the AREVA NC facility at La Hague (France), were used to test Gaussian models of dispersion. In 2001-2002, the French Institute for Radiological Protection and Nuclear Safety (IRSN) studied the atmospheric dispersion of 15 releases, using krypton-85 as a tracer for plumes emitted from two 100-m-high stacks. Krypton-85 is a chemically inert radionuclide. Krypton-85 air concentration measurements were performed on the ground in the downwind direction, at distances between 0.36 and 3.3 km from the release, by neutral or slightly unstable atmospheric conditions. The standard deviation for the horizontal dispersion of the plume and the Atmospheric Transfer Coefficient (ATC) were determined from these measurements. The experimental results were compared with calculations using first generation (Doury, Briggs) and second generation (ADMS 4.0) Gaussian models. The ADMS 4.0 model was used in two configurations; one takes account of the effect of the built-up area, and the other the effect of the roughness of the surface on the plume dispersion. Only the Briggs model correctly reproduced the measured values for the width of the plume, whereas the ADMS 4.0 model overestimated it and the Doury model underestimated it. The agreement of the models with measured values of the ATC varied according to distance from the release point. For distances less than 2 km from the release point, the ADMS 4.0 model achieved the best agreement between model and measurement; beyond this distance, the best agreement was achieved by the Briggs and Doury models.     

基于多源遥感数据及DEM的人口统计数据空间化——以浙江省为例

利用DMSP/OLS遥感夜间灯光数据进行人口等社会经济数据的空间化时,往往受到其较低的空间分辨率、像元过饱和以及像元溢出现象的影响。植被指数（如NDVI）与不透水面呈负相关关系,与夜间灯光数据在反映人类活动、提取建成区方面可以互补,将这两种数据融合可以有效减少夜灯数据像元过饱和等因素引起的误差。通过进一步融合DEM数据对基于DMSP/OLS夜间灯光数据和NDVI构建的人居指数进行了海拔修正,基于修正后的人居指数与统计人口之间很强的线性相关建立人口空间化模型,获得2010年浙江省1 km×1 km分辨率下的人口密度空间分布。模拟结果显示,浙江省平均人口密度为515人/km2,模拟的平均相对误差为183%,相比海拔订正前的模拟误差减少约5%,表明利用多源遥感数据融合后的人居指数在省级尺度上模拟人口空间分布的精度较高     

Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

Effects of white‐nose syndrome on regional population patterns of 3 hibernating bat species

Hibernating bats have undergone severe recent declines across the eastern United States, but the cause of these regional‐scale declines has not been systematically evaluated. We assessed the influence of white‐nose syndrome (an emerging bat disease caused by the fungus Pseudogymnoascus destructans, formerly Geomyces destructans) on large‐scale, long‐term population patterns in the little brown myotis (Myotis lucifugus), the northern myotis (Myotis septentrionalis), and the tricolored bat (Perimyotis subflavus). We modeled population trajectories for each species on the basis of an extensive data set of winter hibernacula counts of more than 1 million individual bats from a 4‐state region over 13 years and with data on locations of hibernacula and first detections of white‐nose syndrome at each hibernaculum. We used generalized additive mixed models to determine population change relative to expectations, that is, how population trajectories differed with a colony's infection status, how trajectories differed with distance from the point of introduction of white‐nose syndrome, and whether declines were concordant with first local observation of the disease. Population trajectories in all species met at least one of the 3 expectations, but none met all 3. Our results suggest, therefore, that white‐nose syndrome has affected regional populations differently than was previously understood and has not been the sole cause of declines. Specifically, our results suggest that in some areas and species, threats other than white‐nose syndrome are also contributing to population declines, declines linked to white‐nose syndrome have spread across large geographic areas with unexpected speed, and the disease or other threats led to declines in bat populations for years prior to disease detection. Effective conservation will require further research to mitigate impacts of white‐nose syndrome, renewed attention to other threats to bats, and improved surveillance efforts to ensure early detection of white‐nose syndrome.     

Using the bootstrap and fast Fourier transform to estimate confidence intervals of 2D kernel densities

Kernel density estimators are often used to estimate the utilization distributions (UDs) of animals. Kernel UD estimates have a strong theoretical basis and perform well, but are usually reported without estimates of error or uncertainty. It is intuitively and theoretically appealing to estimate the sampling error in kernel UD estimates using bootstrapping. However, standard equations for kernel density estimates are complicated and computationally expensive. Bootstrapping requires computing hundreds or thousands of probability densities and is impractical when the number of observations, or the area of interest is large. We used the fast Fourier transform (FFT) and discrete convolution theorem to create a bootstrapping algorithm fast enough to run on commonly available desktop or laptop computers. Application of the FFT method to a large (n>20,000) set of radio telemetry data would provide a 99.6% reduction in computation time (i.e., 1.6 as opposed to 444 hours) for 1000 bootstrap UD estimates. Bootstrap error contours were computed using data from a radio-collared polar bear (Ursus maritimus) in the Beaufort Sea north of Alaska.     

Exploring bicyclist injury severity in bicycle-vehicle crashes using latent class clustering analysis and partial proportional odds models

Introduction: Bicyclists are more vulnerable compared to other road users. Therefore, it is critical to investigate the contributing factors to bicyclist injury severity to help provide better biking environment and improve biking safety. According to the data provided by National Highway Traffic Safety Administration (NHTSA), a total of 8,028 bicyclists were killed in bicycle-vehicle crashes from 2007 to 2017. The number of fatal bicyclists had increased rapidly by approximately 11.70% during the past 10 years (NHTSA, 2019). Methods: This paper conducts a latent class clustering analysis based on the police reported bicycle-vehicle crash data collected from 2007 to 2014 in North Carolina to identify the heterogeneity inherent in the crash data. First, the most appropriate number of clusters is determined in which each cluster has been characterized by the distribution of the featured variables. Then, partial proportional odds models are developed for each cluster to further analyze the impacts on bicyclist injury severity for specific crash patterns. Results: Marginal effects are calculated and used to evaluate and interpret the effect of each significant explanatory variable. The model results reveal that variables could have different influence on the bicyclist injury severity between clusters, and that some variables only have significant impacts on particular clusters. Conclusions: The results clearly indicate that it is essential to conduct latent class clustering analysis to investigate the impact of explanatory variables on bicyclist injury severity considering unobserved or latent features. In addition, the latent class clustering is found to be able to provide more accurate and insightful information on the bicyclist injury severity analysis. Practical Applications: In order to improve biking safety, regulations need to be established to prevent drinking and lights need to be provided since alcohol and lighting condition are significant factors in severe injuries according to the modeling results.     

SEASONAL PUMPING VARIATION EFFECTS ON WELLHEAD PROTECTION AREA DELINEATION1

ABSTRACT: Delineation of a welihead protection area (WHPA) is the key element in welihead protection programs for drinking water supplies. WHPAs are often delineated under idealized conditions using simple steady-state assumptions, which lead to an incorrect estimation of area and geometry. In this paper, we compare the results from a simple steady-state procedure commonly employed in WHPA delineation with a more complex transient approach that allows consideration of seasonal variation in pumping rates. We also introduce a transient procedure to delineate time-related capture zones using a numerical ground water flow and transport model. Welihead delineation is examined for two municipal wells in Tipton, Oklahoma, using a ten-year time-of-travel criterion. In the steady-state procedure, where we assumed constant pumping rates, we used GPTRAC, a semi-analytical model, and MOC, a numerical model. The capture zone delineated by GPTRAC is comparable in shape with the capture zone delineated by MOC but not in size due to the differences in solution schemes. In the transient procedure, we used MOC and considered the seasonal variation in pumping rates. The capture zones delineated in this procedure were larger than the capture zones delineated by the steady-state procedure using the same model. Further analysis showed that a higher drawdown was predicted in the transient procedure than in the steady-state procedure, which is the reason for larger capture zones.     

GOALS AND DATA COLLECTION DESIGNS FOR WATER QUALITY MONITORING1

ABSTRACT: Water quality monitoring cannot address every information need through one data collection procedure. This paper discusses the goals and related procedures for designing water quality monitoring programs. The discussion focuses on the broad information needs of those agencies operating water quality networks. These information needs include the ability to assess trends and environmental impacts, determine compliance with objectives or standards, estimate mass transport, and perform general surveillance. Each of these information needs has different data requirements. This paper outlines these goals and discusses factors to consider in developing a monitoring plan on a site by site basis.