Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region

In this study, hyperspectral reflectance (HySR) data derived from a handheld spectroradiometer were used to assess the water status of three grapevine cultivars in two sub-regions of Douro wine region during two consecutive years. A large set of potential predictors derived from the HySR data were considered for modelling/predicting the predawn leaf water potential (Ψ_pd) through different statistical and machine learning techniques. Three HySR vegetation indices were selected as final predictors for the computation of the models and the in-season time trend was removed from data by using a time predictor. The vegetation indices selected were the Normalized Reflectance Index for the wavelengths 554 nm and 561 nm (NRI_554;561), the water index (WI) for the wavelengths 900 nm and 970 nm, and the D1 index which is associated with the rate of reflectance increase in the wavelengths of 706 nm and 730 nm. These vegetation indices covered the green, red edge and the near infrared domains of the electromagnetic spectrum. A large set of state-of-the-art analysis and statistical and machine-learning modelling techniques were tested. Predictive modelling techniques based on generalized boosted model (GBM), bagged multivariate adaptive regression splines (B-MARS), generalized additive model (GAM), and Bayesian regularized neural networks (BRNN) showed the best performance for predicting Ψ_pd, with an average determination coefficient (R²) ranging between 0.78 and 0.80 and RMSE varying between 0.11 and 0.12 MPa. When cultivar Touriga Nacional was used for training the models and the cultivars Touriga Franca and Tinta Barroca for testing (independent validation), the models performance was good, particularly for GBM (R² = 0.85; RMSE = 0.09 MPa). Additionally, the comparison of Ψ_pd observed and predicted showed an equitable dispersion of data from the various cultivars. The results achieved show a good potential of these predictive models based on vegetation indices to support irrigation scheduling in vineyard.     

Global urbanization projections for the Shared Socioeconomic Pathways

The new scenario process for climate change research includes the creation of Shared Socioeconomic Pathways (SSPs) describing alternative societal development trends over the coming decades. Urbanization is a key aspect of development that is relevant to studies of mitigation, adaptation, and impacts. Incorporating urbanization into the SSPs requires a consistent set of global urbanization projections that cover long time horizons and span a full range of uncertainty. Existing urbanization projections do not meet these needs, in particular providing only a single scenario over the next few decades, a period during which urbanization is likely to be highly dynamic in many countries. We present here a new, long-term, global set of urbanization projections at country level that cover a plausible range of uncertainty. We create SSP-specific projections by choosing urbanization outcomes consistent with each SSP narrative. Results show that the world continues to urbanize in each of the SSPs but outcomes differ widely across them, with urbanization reaching 60%, 79%, and 92% by the end of century in SSP3, SSP2, and SSP1/SSP4/SSP5, respectively. The degree of convergence in urbanization across countries also differs substantially, with largely convergent outcomes by the end of the century in SSP1 and SSP5 and persistent diversity in SSP3. This set of global, country-specific projections produces urbanization pathways that are typical of regions in different stages of urbanization and development levels, and can be extended to further elaborate assumptions about the styles of urban growth and spatial distributions of urban people and land cover occurring in each SSP.     

THE DIRECT EFFECTS OF AEROSOLS AND DECADAL VARIATION OF GLOBAL SEA SURFACE TEMPERATURE ON THE EAST ASIAN SUMMER PRECIPITATION IN CAM3.0

Using the CAM3.0 model, we investigated the respective effects of aerosol concentration increasing and decadal variation of global sea surface temperature(SST) around year 1976/77 on the East Asian precipitation in boreal summer. By doubling the concentration of the sulfate aerosol and black carbon aerosol separately and synchronously in East Asia(100-150 °E, 20-50 °N), the climate effects of these aerosols are specifically investigated. The results show that both the decadal SST changing and aerosol concentration increasing could lead to rainfall decreasing in the center of East Asia, but increasing in the regions along southeast coast areas of China. However, the different patterns of rainfall over ocean and lower wind field over Asian continent between aerosol experiments and SST experiments in CAM3.0 indicate the presence of different mechanisms. In the increased aerosol concentration experiments, scattering effect is the main climate effect for both sulfate and black carbon aerosols in the Eastern Asian summer. Especially in the increased sulfate aerosol concentration experiment, the climate scattering effect of aerosol leads to the most significant temperature decreasing, sinking convection anomalies and decreased rainfall in the troposphere over the central part of East Asia. However, in an increased black carbon aerosol concentration experiment, weakened sinking convection anomalies exist at the southerly position. This weakened sinking and its compensating rising convection anomalies in the south lead to the heavy rainfall over southeast coast areas of China. When concentrations of both sulfate and black carbon aerosols increase synchronously, the anomalous rainfall distribution is somewhat like that in the increased black carbon concentration aerosol experiment but with less intensity.     

Spatial spillover and the socio-ecological determinants of diabetes-related mortality across US counties

The spatial structure of diabetes-related mortality in US counties is evident from previous studies. However, it is not clear if spatial variation in diabetes-related mortality is associated with spatial variation in socioecological factors. We analyze the spatial spillover effect of changes in socioeconomic gradients (education, employment, household income), retail food environments, and access to health care, on diabetes-related mortality rates across the United States. Seven-year aggregates of multiple cause mortality data from the CDC WONDER compressed mortality database were merged with several sources of county-level data to examine mortality clusters, factors associated with the clusters, and spatial spillover effects in 3109 continuous US counties. The results suggest that high diabetes-related mortality cluster counties are located throughout the Southern Plains, Southeastern, and Appalachian regions. Lower socioeconomic status, a high density of fast food restaurants, a lack of access to grocery stores, a high proportion of Blacks, and low physical activity characterize high diabetes-related mortality rates clusters. The impacts from improvements in socioeconomic gradients and the retail food environment in neighboring counties spill over, and reduce the diabetes-related mortality rate in a particular county. This result implies that improvements in socioeconomic status and access to healthy food would significantly reduce diabetes-related mortality rates in contiguous US counties.     

Coverage inequality and quality of volunteered geographic features in Chinese cities: Analyzing the associated local characteristics using geographically weighted regression

The volunteered geographic information (VGI) gains increasing popularity with the general public and scientific community. However, the optimism about the VGI has been tempered by two critical issues: inequality in data coverage (social justice) and data quality. It therefore requires a better understanding of the mechanism driving VGI contributions and content quality. With a case of China, this paper demonstrates one potential avenue, examining the associations between VGI coverage/quality and local demographic and socioeconomic characteristics. In particular, VGI data are harvested from the OpenStreetMap for 333 cities in China. VGI coverage is measured by the total volume of different geographic features (point, line and polygon); and VGI quality is described from two aspects: completeness and accuracy. Geographically weighted regression (GWR) shows that both demographic and socioeconomic factors have statistically significant influences on VGI coverage and quality. More specifically, densely populous cities with more young, educated and non-agricultural people enjoy higher VGI coverage and quality. Cities with lower VGI coverage and quality are primarily located in the western and southwestern regions where the ethnic minorities concentrate. High VGI coverage and quality are possibly observed in economically developed cities with high marketization degree. Besides, possibility of high VGI coverage and quality occurs in cities with more labor in scientific research and greater percentage of employers in the tertiary industry. The GWR also demonstrates that the strength and nature of the obtained relationships vary across the 333 cities. The spatial non-stationary relationships may partially answer for the controversial empirical conclusions in earlier case studies at different scales. Quantitative analysis (Gini index, Lorenz curve and Moran's I index) further evidences the great inequality in VGI coverage and quality. It can be safely inferred that the differences in engagement and use of VGI, as a new digital divide, can raise troubling concerns on the social justice implications.     

The relationship between obesity and socioeconomic status among Texas school children and its spatial variation

Understanding the relationships between obesity and socioeconomic status (SES) among school children and the spatial variation of such relationship is essential for developing appropriate intervention strategies. In this study, we employed Local Entropy Map (LEM) to explore the spatial patterns of the relationship at school district level in Texas. Children's obesity was measured by Body Mass Index (BMI). The BMI data for this study were obtained from Physical Fitness Assessment Initiative (PFAI) program that has been coordinated by Texas Education Agency (TEA). SES was described by six variables, which were further reduced into two factors, namely Household SES and Neighborhood SES. The study period was 2012–2013 academic year. LEM analyses revealed clear spatial variation of the relationship between obesity and SES at school-district level. In particular, the prevalence of obesity among school children was found to be significantly related to Household SES and Neighborhood SES in four regions in Texas. These four regions are centered in major metropolitan areas in Texas, including San Antonio, Dallas-Fort Worth, Houston, and Lubbock. Further regression analyses showed variation of the relationship across these four regions. Obesity among school children in Texas was found to be more related to Household SES than Neighborhood SES; the relationship was strongest in San Antonio region. These findings may suggest the presence of obesogenic environment in the low SES school districts in these regions. Further studies to examine the particular nature of the obesogenic environment in these school districts are needed in order to support the development of regionalized policy and practice that can be more effective in addressing locale specifics.     

Diversity patterns in macrobenthos across a continental slope in the NE Atlantic

Different estimates were used to assess the diversity of the total macrofauna and its major taxonomic groups separately from a broad bathymetric range at a site in the NE Atlantic. In the Goban Spur region, a transect was sampled from the shelf to the abyssal plain over a depth range from 200 to 4500 m and in the Porcupine Sea Bight two stations were sampled (at 3670 m and 4115 m). Species diversity (the number of species per number of individuals) increased with increasing water depth, both when expressed as Hurlbert's E(S_n) and as Shannon's H′log e. The expected number of species in a 100-individual sample E(S₁₀₀) of total macrofauna increased from 30 on the shelf to 68 on the abyssal plain. Evenness (the proportional abundance of species), estimated with Shannon's J′, also increased with water depth from 0.66 to 0.91, whereas dominance (Simpson's D) decreased from 0.09 to 0.01. Species richness (the number of species per unit of area), however, showed a parabolic pattern with a peak at the upper slope. The largest number of species was found at the slope station at 1425 m (232 species within 0.66 m²). It is argued that species richness is not a synonym of species diversity, but that species richness depends both on species density (which decreases with increasing water depth) and on species diversity. Across the whole bathymetric range (200 to 4500 m) a total of 696 species within 8327 specimens in a total sampled area of 4.12 m² were counted, yielding mean values of 12 individuals per species and 169 species per m². Different communities were found to exist on the shelf, slope and abyss. It is suggested that this could have been caused by different selection processes. Differences in life-history strategies and organic-matter supply could (at least partly) explain the different community structures and diversity patterns found along the depth gradient.     

福建省前汛期旱涝年前冬季500hPa高度场特征及其与东亚冬季风的关系

通过对1961～2001年福建前汛期降水与东亚前冬季冬季风强弱与副高强度间的相关性等统计分析表明：前冬季冬季风强（弱）年，前汛期西太平洋副高偏弱（强），福建降水偏多（少），此外，本文利用ECMWF再分析资料，对比分析了旱涝年份前冬季500hPa环流形势差异．其结果显示：旱（涝）年前冬季，东亚大槽偏弱（强），冬季风减弱（增强），副热带高压偏强（弱）。     

气候变暖背景下黄河流域干旱灾害风险空间特征

黄河流域是中国重要的经济带和经济增长极,也是人口密集暴露、特色农业种植和重点生态承载区。在全球变暖和极端降水事件频发的气候背景下,近年来黄河流域干旱灾害变化特征异常突出,新形势下该流域的干旱灾害风险及其对气候变化的响应机制需进一步深入认识。本文利用1960年以来黄河流域122个国家气象站逐日气象数据,结合遥感、社会统计和地理信息数据与技术,基于灾害风险理论,建立致灾因子危险性、孕灾环境脆弱性、承灾体易损性和防灾减灾能力可靠性4个因子的干旱灾害风险指标体系和模型,详细分析了黄河流域干旱灾害风险变化特征和区域差异性及其气候变化的影响机制。结果表明：黄河流域干旱灾害风险分布格局具有明显的地带性和复杂性,流域区域差异显著,总体是中下游风险高于上游,高风险区主要位于黄河流域中下游,致灾因子危险性是黄河流域干旱灾害风险的主导因子,其次是孕灾环境脆弱性和防灾减灾能力可靠性,而承灾体易损性贡献量相对最小。干旱灾害风险影响机制的区域差异也很显著,上游是孕灾环境脆弱性和防灾减灾能力可靠性的影响大于致灾因子和易损性,中游则是致灾因子、易损性和防灾减灾能力对干旱灾害风险的贡献度大,下游是干旱致灾因子起主导作用,致灾因子危险性和承灾体易损性控制了风险总体格局。黄河流域干旱灾害风险变化规律以及对气候变化的响应异常复杂,流域干旱灾害风险主要受季风气候和复杂地形的影响,还受社会经济发展水平、人口暴露度和水资源供需矛盾等多种要素的影响。该研究对黄河流域生态文明建设,粮食安全保障和国家发展战略具有重要意义。     

S2S气候模式产品在黄河流域径流预测中的应用

次季节气候和径流预测是主动减灾的一个关键。基于国家气候中心第三代气候模式系统的次季节到季节模式(CMA-CPS v3 S2S)的气候预测信息和HBV水文模型,应用集合预测技术研发了未来40 d时段平均径流量和时段内极端干旱概率预测模型,应用平均方差技巧评分、距平相关系数、相对操作特征曲线面积、布赖尔技巧评分开展了回报检验,并检验了2021年黄河流域径流异常预测效果。结果表明,所建模型能够以较高技巧预测黄河流域未来40 d时段平均的径流量,且表现出枯季预测技巧高、湿季技巧低的季节差异;对秋末11月和冬季3个月(12月、1月、2月)的极端干旱概率预测也有较高技巧。对于2021年5—8月黄河上中游干旱和9—10月的秋汛,该方法正确预测了除6月、9月外的其他4个月的径流异常方向,但异常程度与实况存在差异。对径流预测水平影响因素的进一步分析表明,S2S降水预测能力影响径流预测水平,特别是丰水期的径流预测,但还有降水之外的其他因素影响径流预测技巧。