Spatial patterns of subsistence extraction of forest products – An indirect approach for estimation of forest degradation in dry forest

Successful implementation of a forest based climate change mitigation mechanism such as REDD + depends on robust and available methods for measurement and estimation of forest degradation. Currently available methods are for application in single-hit degradation incidents in high density humid forests. However, it has been suggested that gradual degradation, especially in dry forests, is more widespread and that methods are needed for measuring and estimating associated emissions. We assess the applicability of an indirect remote sensing approach for monitoring forest degradation: infrastructure and other indicators of human activities are mapped and used for spatial prediction of degradation activities. For proxy variables we tested distance to forest edge, distance to roads, and population pressure calculated as the sum of inhabitants per pixel in the Landscan 2010 population raster dataset multiplied by an inverse power distance decay function. Wood extraction incidents were counted in 160 plots in two dry forests in Tanzania with infrastructural entry from one side only. We analyzed the spatial pattern of forest degradation as a function of the chosen proxy variables using zero inflated count models which allows for an excess of zero counts. A jack-knife bootstrap using 10,000 runs was applied to optimize the population distance decay function. We found that the impact of forest degradation is highest near high population concentration, above 1000 individuals. Furthermore, distance to nearest forest edge or road was a significant proxy for estimation of the number of wood extraction incidents (p < 0.001), where degradation incidents decreased with increasing distance to forest edge or road. At 3000 m from the forest edge towards the forest core the probability of wood extraction is 20% and dropping. The population distance decay function was found to have a steep decline indicating a relative small impact on forest degradation. Further, and perhaps larger, studies are needed to be able to recommend a distance decay function for general application in Tanzania. However, the results are useful for understanding spatial patterns of wood harvesting as a function of distance to nearest forest edge or road in dry Miombo woodland areas with average population pressure at 1685 ± 101 persons within a radius of 4000 m from the wood extraction sites.     

济南市人口城镇化与土地城镇化协调发展研究

人口城镇化与土地城镇化协调发展是推进新型城镇化的重点所在。通过构建指标评价体系和评价模型,从“人口-土地”协调的视角分析演算1995-2013年济南市的城镇化水平与协调发展状态。研究结果表明,济南市城镇化整体协调发展度从1995年的严重失调衰退阶段发展到2013年的优质协调发展阶段,但是从2008开始,人口城镇化滞后于土地城镇化发展,表现出一定的失调现象。研究结果可以为制定地区城镇化发展策略提供科学依据。     

Multitemporal settlement and population mapping from Landsat using Google Earth Engine

As countries become increasingly urbanized, understanding how urban areas are changing within the landscape becomes increasingly important. Urbanized areas are often the strongest indicators of human interaction with the environment, and understanding how urban areas develop through remotely sensed data allows for more sustainable practices. The Google Earth Engine (GEE) leverages cloud computing services to provide analysis capabilities on over 40 years of Landsat data. As a remote sensing platform, its ability to analyze global data rapidly lends itself to being an invaluable tool for studying the growth of urban areas. Here we present (i) An approach for the automated extraction of urban areas from Landsat imagery using GEE, validated using higher resolution images, (ii) a novel method of validation of the extracted urban extents using changes in the statistical performance of a high resolution population mapping method. Temporally distinct urban extractions were classified from the GEE catalog of Landsat 5 and 7 data over the Indonesian island of Java by using a Normalized Difference Spectral Vector (NDSV) method. Statistical evaluation of all of the tests was performed, and the value of population mapping methods in validating these urban extents was also examined. Results showed that the automated classification from GEE produced accurate urban extent maps, and that the integration of GEE-derived urban extents also improved the quality of the population mapping outputs.     

城镇化背景下中国长期低碳转型路径研究

在中国经济步入新常态之际,为了研究城镇化背景下的长期碳排放趋势,构建了人口变动与能源系统互动的综合分析框架与社会经济-能源系统模型。结果显示,从2014年至2050年,预计有3亿人口从农村流向城市,并呈现从中小型城市逐步向大型和特大型城市汇集的趋势。人口流动趋势与人民生活质量改善结合,推动中国基础设施建设、工业产品生产和能源服务需求增长。基准情景下,2050年中国一次能源消费总量达到84亿tce,能源相关CO₂排放达到176亿t,比2013年增长83%;而在低碳转型情景下,通过技术创新,2050年中国一次能源消费需求可以控制在61亿tce左右,CO₂排放在2020—2025年间达峰,2050年比基准情景降低78%。低碳转型过程中,非化石能源电力和能效技术的减排潜力最大,工业和电力部门率先在2020年达峰,建筑和交通 ^①（①按照国际通行的能源系统部门划分标准和能耗概念,工业、建筑、交通均属于终端能源消费部门,其中建筑部门能耗指建筑运行能耗,而非建筑建造过程中的能耗;交通部门能耗指所有交通活动能耗,既包括交通运输业营运类运输工具的交通能耗,也包括私人、公务非营运类运输工具的交通能耗 ^[1]。）将在2030年左右达峰。实现低碳转型所需新增固定投资占GDP的1.5%,不会给国民经济带来重大负担。中国实施新型城镇化战略具有技术和经济可行性。     

The climate-population nexus in the East African Horn: Emerging degradation trends in rangeland and pastoral livelihood zones

Increasing climate variability and extreme weather conditions along with declining trends in both rainfall and temperature represent major risk factors affecting agricultural production and food security in many regions of the world. The rangelands of Ethiopia, Kenya, and Somalia in the East African Horn remain one of the world's most food insecure regions, yet have substantially increasing human populations predominantly dependent on pastoralist and agro-pastoralist livelihoods. We identify regions where substantial rainfall decrease between two periods interrupted by the 1998 El Nino event (1981–2012) in the East African Horn is coupled with human population density increases. Vegetation in this region is characterized by a variable mosaic of land covers, generally dominated by grasslands necessary for agro-pastoralism, interspersed by woody vegetation. Recent assessments indicate that vegetation degradation is occurring, adversely impacting fragile ecosystems and human livelihoods. Using AVHRR and MODIS vegetation products from 1981 to 2012, we observe changes in vegetation patterns and productivity over the last decade across the East African Horn. We observe vegetation browning trends in areas experiencing reduced main-growing season precipitation; these areas are also concurrently experiencing increasing population pressures. We also found that the drying precipitation patterns only partially statistically explain the vegetation browning trends, indicating that other factors such as population pressures and land use changes might be responsible for the observed declining vegetation condition. Furthermore, we show that the general vegetation browning trends persist even during years with normal rainfall conditions such as 2012, pointing to potential long-term degradation of rangelands on which approximately 10 million people depend. These findings may have implications for current and future regional food security monitoring and forecasting as well as for mitigation and adaptation strategies in a region where population is expected to continue increasing against a backdrop of drying climate trends and increased climatic variability.     

A Statistical Model for Predicting the Average Abundance Patterns of Heavier Elements in Metal-Poor Stars

We have collected nearly all the available observed data of the elements from Ba to Dy in halo and disk stars in the metallicity range -4.0 <[Fe/H]< 0.5. Based on the observed data of Ba and Eu, we evaluated the least-squares regressions of [Ba/Fe] on [Fe/H], and [Eu/H] on [Ba/H]. Assuming that the heavy elements (heavier than Ba) are produced by a combination of the main components of s- and r-processes in metal-poor stars, and choosing Ba and Eu as respective representative elements of the main s- and the main r-processes, a statistical model for predicting the Galactic chemical evolution of the heavy elements is presented. With this model, we calculate the mean abundance trends of the heavy elements La, Ce, Pr, Nd, Sm, and Dy with the metallicity. We compare our results with the observed data at various metallicities, showing that the predicted trends are in good agreement with the observed trends, at least for the metallicity range [Fe/H]> -2.5. Finally, we discuss our results and deduce some importa     

Rural household demographics, livelihoods and the environment

This paper reviews and synthesizes findings from scholarly work on linkages among rural household demographics, livelihoods and the environment. Using the livelihood approach as an organizing framework, we examine evidence on the multiple pathways linking environmental variables and the following demographic variables: fertility, migration, morbidity and mortality, and lifecycles. Although the review draws on studies from the entire developing world, we find the majority of microlevel studies have been conducted in either marginal (mountainous or arid) or frontier environments, especially Amazonia. Though the linkages are mediated by many complex and often context-specific factors, there is strong evidence that dependence on natural resources intensifies when households lose human and social capital through adult morbidity and mortality, and qualified evidence for the influence of environmental factors on household decision-making regarding fertility and migration. Two decades of research on lifecycles and land cover change at the farm level have yielded a number of insights about how households make use of different land-use and natural resource management strategies at different stages. A thread running throughout the review is the importance of managing risk through livelihood diversification, ensuring future income security, and culture-specific norms regarding appropriate and desirable activities and demographic responses. Recommendations for future research are provided.     

The depletion of carbon by extra mixing in metal-poor giants

There is an apparent dichotomy between the metal-poor  ([Fe/H]≤−2)  yet carbon-normal giants and their carbon-rich counterparts. The former undergo significant depletion of carbon on the red giant branch after they have undergone first dredge-up, whereas the latter do not appear to experience significant depletion. We investigate this in the context that the extra mixing occurs via the thermohaline instability that arises due to the burning of  ³He  . We present the evolution of [C/Fe], [N/Fe] and  ¹²C/¹³C  for three models: a carbon-normal metal-poor star, and two stars that have accreted material from a  1.5 M_⊙  AGB companion, one having received  0.01 M_⊙  of material and the other having received  0.1 M_⊙  . We find the behaviour of the carbon-normal metal-poor stars is well reproduced by this mechanism. In addition, our models also show that the efficiency of carbon-depletion is significantly reduced in carbon-rich stars. This extra-mixing mechanism is able to reproduce the observed properties of both carbon-normal and carbon-rich stars.     

Distinguishing breeding populations of mallards (Anas platyrhynchos) using trace elements

The knowledge of connectivity among breeding and overwintering populations of migratory bird species is critical for the conservation of their habitats. Conventional field work for the tracking of migratory birds involving bird banding often yields poor results due to low recovery rates, or is expensive when satellite tracking methods are used. Intrinsic tools such as genetic markers, stable isotopes, strontium isotopes and trace elements have been successfully used for tracing origins and/or migratory pathways of bird populations. We studied elemental signatures in the tail feathers to group breeding populations and an overwintering population of Mallards (Anas platyrhynchos). Tail feathers from five locations in Canada and the U.S. were analyzed using Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS). We used 18 elements to discriminate between Mallard populations. Linear discriminant analysis on a selected set of elements demonstrated that 93% of the Mallards could be accurately located back to their predicted locations. Mallard feathers from Arkansas (an important overwintering area), grouped together with any combination of elements as predictors. We predicted the breeding locations of overwintering Mallards from Arkansas. Our results confirm that the LA-ICP-MS technique shows high potential to estimate the origin of migratory animals.