Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging

Accurately mapping the spatial distribution of soil total nitrogen is important to precision agriculture and environmental management. Geostatistical methods have been frequently used for predictive mapping of soil properties. Recently, a local regression method, geographically weighted regression (GWR), got the attention of environmentalists as an alternative in spatial modeling of environmental attributes, due to its capability of incorporating various auxiliary variables with spatially varied correlation coefficients. The objective of this study is to compare GWR and ordinary cokriging (OCK) in predictive mapping of soil total nitrogen (TN) using multiple environmental variables. 353 soil Samples within the surface horizon of 0–20 cm in a study area were collected, and their TN contents were measured for calibrating and validating the GWR and OCK interpolations. The environmental variables finally chosen as auxiliary data include elevation, land use types, and soil types. Results indicate that, although OCK is slightly better than GWR in global accuracy of soil TN prediction (the adjusted R² for GWR and OCK are 0.5746 and 0.6858, respectively), the soil TN map interpolated by GWR shows many details reflecting the spatial variations of major auxiliary variables while OCK smoothes out almost all local details. Geographically weighted regression could account for both the spatial trend and local variations, whilst OCK had difficulties to capture local variations. It is concluded that GWR is a more promising spatial interpolation method compared to OCK in predicting soil TN and potentially other soil properties, if a suitable set of auxiliary variables are available and selected.     

Empirical models of rain-spells characteristics – A case study of a Mediterranean-arid climatic transect

Environmental (geomorphological, hydrological and ecological) processes are controlled by rainfall, particularly in the Mediterranean, semi-arid and arid regions. Rainfall was analyzed using the concept of rain-spells, i.e., a period of successive rain days preceded and followed by at least one day without rainfall. Daily data from 13 stations along a climatic transect extending from the Judean Mountains with a Mediterranean climate to the Dead Sea arid region in Israel were studied. Rain-spell characteristics (number, yield and duration), based on these data, are presented for different rainfall thresholds, which might be used for different environmental processes such as rock weathering, soil organic matter dynamics, landslides, overland flow and floods and soil erosion. Three estimation models have been developed in order to predict the mean annual Number of Rain-Spells (NRS), mean Rain-Spell Yield (RSY), and mean Rain-Spell Duration (RSD) for the mean annual rainfall and for any given rainfall threshold. These models can be used for current climatic conditions and for scenarios in which the rainfall total changes.     

Variation in low food access areas due to data source inaccuracies

Several spatial measures of community food access identifying so called “food deserts” have been developed based on geospatial information and commercially-available, secondary data listings of food retail outlets. It is not known how data inaccuracies influence the designation of Census tracts as areas of low access. This study replicated the U.S. Department of Agriculture Economic Research Service (USDA ERS) food desert measure and the Centers for Disease Control and Prevention (CDC) non-healthier food retail tract measure in two secondary data sources (InfoUSA and Dun & Bradstreet) and reference data from an eight-county field census covering 169 Census tracts in South Carolina. For the USDA ERS food deserts measure accuracy statistics for secondary data sources were 94% concordance, 50–65% sensitivity, and 60–64% positive predictive value (PPV). Based on the CDC non-healthier food retail tracts both secondary data demonstrated 88–91% concordance, 80–86% sensitivity and 78–82% PPV. While inaccuracies in secondary data sources used to identify low food access areas may be acceptable for large-scale surveillance, verification with field work is advisable for local community efforts aimed at identifying and improving food access.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

Climate-induced change of environmentally defined floristic domains: A conservation based vulnerability framework

Global climate change is having marked influences on species distributions, phenology and ecosystem composition and raises questions as to the effectiveness of current conservation strategies. Conservation planning has only recently begun to adequately account for dynamic threats such as climate change. We propose a method to incorporate climate-dynamic environmental domains, identified using specific environmental correlates of floristic composition, into conservation strategies, using the province of KwaZulu-Natal, South Africa as a case study. The environmental domains offer an approach to conservation that conserves diversity under current and future climates, recognising that the species constituting diversity may change through time. We mapped current locations of domains by identifying their positions in a multi-dimensional environmental space using a non-hierarchical iterative k-means clustering algorithm. Their future locations were explored using an ensemble of future climate scenarios. The HadCM2 and GFDL2.1 models represented the extreme ranges of the models. The magnitude of change in each environmental domain was calculated using Euclidean distances to determine areas of greatest and least stability for each future climate projection. Domains occurring in the savanna biome increase at the expense of domains occurring in the grassland biome, which has significant negative consequences for the species rich grasslands. The magnitude of change maps represents areas of changed climatic conditions or edaphic disjunctions. The HadCM2 model predicted the greatest overall magnitude of change across the province. Species with specific soil requirements may not be able to track changing climatic conditions. A vulnerability framework was developed that incorporated climatic stability and habitat intactness indices. The mean magnitude of change informed the potential speed of transition of domains between the vulnerability quadrants. The framework informs appropriate conservation actions to mitigate climate change impacts on biodiversity. The study explicitly links floristic pattern and climate variability and provides useful insights to facilitate conservation planning for climate change.     

Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city,China

Land price plays an important role in guiding land resource allocation for urban planning and development, particularly in big cities of fast developing countries where infrastructures and populations change frequently. Therefore, detecting spatially implicit information in the spatial pattern of relationships between land price and related impact factors is critical. Geographically weighted regression (GWR) analysis was conducted in this study for the purpose in Wuhan, China, by using a 10-year panel data set of residential land price. Based on twelve factors in three aspects (land attributes, location factors and neighborhood attributes), an evaluation index system of resident land price was established. The spatial distributions of estimated coefficients and pseudo t-values of three major explanatory variables (floor area ratio, distance to nearest center business district (CBD) and distance to nearest lake), obtained from GWR analysis, indicated that their relationships of the impact factors with land price are spatially non-stationary. The positive impact of floor area ratio on land price is more significant in highly developed areas than in less developed areas. Conversely, the negative impact of distance to nearest CBD on land price is larger in highly developed areas than in less developed areas. Moreover, wealthier dwellers may be willing to pay a higher price for a good lake view (especially views of small lakes), but infrastructure barriers (near some large lakes) cause negative effect. The outputs of this study, which provide detailed information on the relationships between land price and impact factors in local areas, are promising for urban planners to scientifically evaluate land price and make area-specific strategies.     

Lessons learned from the 2013 Calgary flood: Assessing risk of drinking water well contamination

A devastating flood occurred in southern Alberta on June 19, 2013, from greater than normal snowfalls in the Rocky Mountains and excess precipitation during the early spring that left soils saturated and unable to absorb any additional precipitation. This flood was Canada's most costly natural disaster, with five to six billion Canadian dollars in damages. The first objective of this study was to determine if the flood caused an increase in private drinking water well contamination in the Calgary Health Zone by comparing contamination rates to previous years. The second objective was to determine which environmental factors were associated with contamination during this flood event. Test results of total coliforms (TC) and Escherichia coli (EC) of private water wells were used to determine contamination. A geographically weighted Poisson regression analysis suggested that TC contamination was not associated with this flood. The EC contamination is positively associated with floodways, flood fringe, farms, and negatively associated with intermittent water (sloughs). These results suggest that for the 2013 flood, individual well characteristics are more important than surrounding geographic features. Thus, it is recommended that homeowners who live in a high-risk area ensure their wells are properly maintained to reduce risk of water well contamination.     

Boundary-based analysis for the assessment of coastal dune landscape integrity over time

Coastal dunes are transitional systems which offer manifold ecosystem services, including material and intangible benefits, whose relevance for human society has been little investigated to date. In order to plan a sustainable use of these threatened ecosystems, proper indicators to quantify ecological services and functions over time should be provided. Since the functionality of coastal dunes is affected by the specific contiguity among different dune habitat patches, in this paper we propose the use of landscape integrity, expressed by the number and length of boundary types among the aforementioned habitats, as an ecosystem functionality indicator. In particular, we aim at properly expressing the trend of coastal dune mosaic integrity in two Italian LTER sites over the last sixty years by applying a generalized diversity function on the number and length of boundary types. Such functions, unlike a traditional diversity index, allow a complete summarization of landscape diversity and structure. The proposed method has proved to be effective in the considered context, because it has adequately underlined the different landscape integrity trend recorded in the two sites. In particular, generalized diversity functions showed to efficiently express both rough and moderate anthropogenic transformations, which affected spatial heterogeneity and functionality of the considered coastal dune mosaic. Further applications at different scales and across different ecosystems are encouraged.     

Soil seed bank longevity of the exotic annual grass Bromus rubens in the Mojave Desert,USA

Although arid environments are often considered among the least invaded terrestrial biomes, the impacts of exotic plant species can be severe and long lasting. Bromus rubens (red brome) is an exotic annual grass species in the Mojave Desert known to outcompete native plant species, alter habitat, and promote accumulation of fuel that contributes to increasing fire frequency and severity. We assessed longevity of the exotic B. rubens seeds in the soil by burying seeds at four depths (0, 2, 5, and 10 cm) and recovering seeds 6, 12, 18, and 24 months after burial. Seed viability was reduced with greater burial depth and greater time since burial. A relatively small proportion of seeds retained viability for two years, suggesting that while the B. rubens seed bank can be large, it is relatively short-lived. Although B. rubens apparently relies more on the annual production, dispersal, and germination of seeds than on a long-lived seed bank for its annual recruitment, the numerous seeds produced by individual plants indicate that even a small proportion of seeds remaining viable for more than a year can aid recruitment from the seed bank and is an important factor in understanding population dynamics.     

Modelling collective Yawuru values along the foreshore of Roebuck Bay,Western Australia using fuzzy logic

The cadastral model has played a key role in Indigenous dispossession in settler states. Yet, the recognition of Indigenous land rights, which has increased globally since the 1960s, frequently requires Indigenous communities to directly engage with this spatial model. In Australia, native title claimants must use entity-based models of space to delineate their traditional territories during the claim process. They must also engage with planning and development documents which use the cadastral model of space to assert and defend their rights following native title recognition. This is often problematic as Indigenous spatial ontologies emphasise complexity and continuity which is inimical to the ‘crisp’ representations of cadastral space.This study explores the potential of a fuzzy index modelling approach to represent cultural values using a case study from Broome, Western Australia. Sketch mapping, fuzzy index modelling and combinatory techniques were used to produce a model of several cultural values held by the Yawuru community for the in-town foreshore of Roebuck Bay. This model was overlaid on local planning documents to provide the Yawuru community with strategic intelligence for post native title governance. The experience of co-producing this model suggests that such techniques may assist Indigenous communities to engage with settler structures. This implies that policies which fail to extend analytical capacity to interested native title groups as part of programmes of spatial enablement continue to perpetuate historical processes of colonial domination.     

Benefits of mycorrhizal inoculation in reintroduction of endangered plant species under drought conditions

Numerous human activities constitute threats to biodiversity. The effects of climate change, including increasing drought in already arid lands, pose an additional layer of uncertainty in the fate of rare species. In the case of plants, reintroduction is becoming an important active management practice in species conservation. We hypothesized that even under extreme drought inoculation with mycorrhizal fungi would increase growth rates of an endangered plant in experimental reintroduction. We selected a plant species, Abronia macrocarpa, and conducted the experiment in Texas while the area was experiencing mild and extreme drought intensities. Treatment plots were planted with seed inoculated with arbuscular mycorrhizal fungi and control plots were planted with seed coated with autoclaved inoculant. We analyzed measurements of growth and development of germinated plants. Mean number of leaves was greater in treatment plants (P = 0.005) and mean aerial diameter was larger in treatment plants (P = 0.02) than in control plants. Significantly improved growth suggests that inoculation is a viable technique to increase reintroduction success in plant species especially during periods of drought.     

A comparison of techniques for generating forest ownership spatial products

To fully understand forest resources, it is imperative to understand the social context in which the forests exist. A pivotal part of that context is the forest ownership. It is the owners, operating within biophysical and social constraints, who ultimately decide if the land will remain forested, how the resources will be used, and by whom. Forest ownership patterns vary substantially across the United States. These distributions are traditionally represented with tabular statistics that fail to capture the spatial patterns of ownership. Existing spatial products are not sufficient for many strategic-level planning needs because they are not electronically available for large areas (e.g., parcels maps) or do not provide detailed ownership categories (e.g., only depict private versus public ownership). Thiessen polygon, multinomial logit, and classification tree methods were tested for producing a forest ownership spatial dataset across four states with divergent ownership patterns: Alabama, Arizona, Michigan, and Oregon. Over 17,000 sample points with classified forest ownership, collected as part of the USDA Forest Service, Forest Inventory and Analysis (FIA) program, were divided into two datasets, one used as the dependent variable across all of the models and 10 percent of the points were retained for validation across the models. Additional model inputs included a polygon coverage of public lands from the Conservation Biology Institute’s Protected Areas Database (PAD) and data representing human population pressures, road densities, forest characteristics, land cover, and other attributes. The Thiessen polygon approach predicted ownership patterns based on proximity to the sample points in the model dataset and subsequent combining with the PAD ownership data layer. The multinomial logit and classification tree approaches predicted the ownership at the validation points based on the PAD ownership information and data representing human population, road, forest, land cover, and other attributes. The percentage of validation points across the four states correctly predicted ranged from 76.3 to 78.9 among the methods with corresponding weighted kappa values ranging from 0.73 to 0.76. Different methods performed slightly, but statistically significantly, better in different states Overall, the Thiessen polygon method was deemed preferable because: it has a lower bias towards dominant ownership categories; requires fewer inputs; and is simpler to implement.     

Photosynthetic characteristics of sinking microalgae under the sea ice

The photosynthetic characteristics of sinking a microalgal community were studied to compare with the ice algal community in the sea ice and the phytoplankton community in the water column under the sea ice at the beginning of the light season in the first-year sea ice ecosystem on the Mackenzie Shelf, in the western Canadian Arctic. The phytoplankton community was collected using a water bottle, whereas the sinking algal community was collected using particle collectors, and the ice algal community was obtained by using an ice-core sampler from the bottom portion of ice core. Photosynthesis versus irradiance (P-E) incubation experiments were conducted on deck to obtain the initial slope (α^B) and the maximum photosynthetic rate (P_m^B) of the three algal communities. The α^B and the P_m^B of the light saturation curve, and chlorophyll a (Chl a) specific absorption coefficient (ā_ph*) between the sinking microalgal community and the ice algal community were similar and were distinctly different from the phytoplankton community. The significant linear relationship between α^B and P_m^B, which was obtained among the three groups, may suggest that a photo-acclimation strategy is common for all algal communities under the low light regime of the early season. Although the sinking algal community could be held for the entire duration of deployment at maximum, this community remained photosynthetically active once exposed to light. This response suggests that sinking algal communities can be the seed population, which results in a subsequent phytoplankton bloom under the sea ice or in a surface layer, as well as representing food for the higher trophic level consumers in the Arctic Ocean even before the receding of the sea ice.     

The Best of Times and the Worst of Times: Structural Adjustment Programs and Uneven Development in Africa: The Case Of Ghana

Since 1983, Ghana has been undergoing World Bank and International Monetary Fund (IMF) sponsored Structural Adjustment Programs (SAPs). The implementation of the SAPs, it is claimed, has arrested Ghana's economy from complete collapse, resulted in consistent growth in GDP averaging 6% over the past decade, reduced inflation levels, created budget surplus, and increased export earnings. Compared to the 1970s, these are the best of times indeed. But while these SAPs‐derived improvements in the national economy have been recorded at the macro level, the benefits at the micro level are a matter of considerable debate. This study revisits the issue of socioeconomic and spatial disparities that have characterized Ghana since colonial times, emphasizing the period from 1983 when Ghana's SAPs began. It examines current patterns of socioeconomic disparities with emphasis on the distribution of, and access to, health, education, basic services, and the like. The study focuses on urban‐rural as well as interregional disparities in the country.     

20世纪90年代以来欧美人文地理学(导论)教材编写新趋向及其启示

基于对欧美人文地理学（导论）教材出版的新情况,对相关问题作些尝试性的探讨,以期为编写出优秀且符合时代要求的人文地理学（导论）教材提供一些参考。欧美同类教材的趋向：① 在原有多样化的基础上重构;② 概念主导的教材在增长;③ 概念主导教材的作者在增多。这些新动向给我们的启示：① 针对多样化的需要,编出多样化的导论教材;② 加强教材的学术性和思想性;③ 教材写作要突出基本概念,培养地理学思维。     

基于义务教育校际分异的学校类型及其空间分布模式——以大连市初中为例

利用2015年大连市初中学校多维数据,在分析社会群体间分异状况及其空间表现的基础上,概括了学校的基本类型及其空间分布特征,总结了义务教育校际分异的空间模式。在市域范围内存在4类学校,即成绩较好的城市综合社会群体子女学校;成绩一般的产业工人及一般技术人员子女学校;成绩优异的教师、政府和企事业单位管理者及专业技术人员子女学校;成绩落后但生均教育资源充沛的农村地区学校。4类学校在市域范围内分异明显,形成了从内向外的5个教育圈,即城市中心教育圈、城市郊区教育圈、城市新区教育圈、外围城镇教育圈和外围乡村教育圈。教育资源在教育圈之间呈高低相间分布的特点,教学成绩和学生家庭社会经济地位呈现出从中心向外围逐步降低的特征。     

基于等级合理性和居业协同度的村庄类型识别与振兴路径研究

村镇体系是乡村要素集聚与实施乡村振兴战略的空间载体,通过判断村镇体系与乡村振兴之间的逻辑关系,探索不同类型农区村镇体系的空间优化路径,对于科学推进乡村振兴战略具有重要指导意义。论文利用江苏省丰县356个村庄、14个镇的多源数据,从等级合理度与居业协同度2个维度构建村镇体系评价体系,探析了村镇人口、农业、非农业要素集聚能力、空间极化特征与居业协同格局,然后基于村庄类型的划分,进一步识别了乡村振兴的空间类型,最后提出了不同空间类型的乡村振兴路径与具体对策。主要研究结论为:① 丰县村镇体系呈现出结构相对稳定、空间极化程度不高、局部地区居业相对失衡、乡村振兴内在动力不足等主要特征;② 结合要素集聚与居业协同特征,将村庄划分为人口—非农业要素滞后的弱就业功能型(I)、人口—农业要素滞后的弱就业功能型(II)、人口—非农业要素相对滞后的低水平居业均衡型(III)、要素相对耦合的高水平居业协同型(IV)、非农业要素滞后的弱居住功能型(V)、农业要素滞后的弱居住功能型(VI)6种类型;③ 基于村庄类型识别结果,进一步甄别了丰县未来推进乡村振兴的核心区、外围区、潜力区,构建了分区分类实施乡村振兴战略的基本思路与具体路径。     

中国城乡基本公共服务均等化及其空间格局分析

以中国31个省级行政单位为研究对象,从教育服务、文化服务、医疗卫生服务、基础设施服务、社会保障服务和信息化服务6个方面构建指标体系,综合测度各省份城市和农村基本公共服务水平;利用信息熵原理构建基本公共服务均等化指数,测度各省份城乡基本公共服务均等化程度,并用探索性空间数据分析方法对城乡基本公共服务均等化指数的空间格局进行研究。研究表明：① 各省份城市和农村基本公共服务水平的差异均十分显著。城市基本公共服务水平的空间分布为“T”字型格局,并呈“东—中—西”阶梯状递减;农村基本公共服务水平的空间分布与城市存在很大的不一致性,呈“东—西—中”阶梯状递减的格局。② 31个省份的城乡基本公共服务均等化指数偏低,其空间分布存在着显著的全局空间自相关特征。③ 各省份农村基本公共服务水平对均等化指数的影响大于城市,城乡基本公共服务均等化指数与农村基本公共服务水平的关系类似马太效应。     

江苏省乡村旅游产业发展水平及空间差异分析

乡村旅游产业是实现乡村旅游经济发展、产业升级、效益增长、环境改善和区域协调的重要载体和有效渠道.基于乡村旅游产业发展相关统计数据,构建乡村旅游产业发展水平的评价体系,并选择江苏省为案例,借助因子分析法、ESDA法,纵向维度探讨江苏省乡村旅游产业发展演化状况,横向维度动态比较乡村旅游产业发展空间差异,结果表明:2003-2015年江苏省13个辖市乡村旅游产业发展水平均存在变化,其中,先升后降的有苏州、常州等六市,先降后升的有南京、无锡等五市,持续下降的有宿迁和泰州;依据乡村旅游产业发展状况,将13个辖市乡村旅游划分为领先发展、增长潜力、优势提升和滞后发展4种类型;乡村旅游产业发展水平存在区域间变化相对稳定、区域内部差异明显小于区域间差异且沿主轴方向集聚、沿辅轴方向分散的特征;同时乡村旅游产业发展重心呈现先东北后西南的演化趋势.基于分析提出江苏省乡村旅游产业今后发展建议.     

农户层面农村宅基地流转研究进展与述评

农户层面研究对解析人地关系特别是农户与地理环境的相互作用所凸显的优越性与实践性收到学界的广泛推崇,成为当前学者研究农村发展与土地利用问题的重要手段。采用文献回顾法、归纳法,本文对国内外农户层面农村宅基地流转研究进行了归纳与对比分析。研究表明,国内外学者对宅基地流转的讨论对象与研究热点差异明显,研究方法与视角等也略有差异。国外学者对宅基地流转研究的关注度尚不多,已有成果主要集中在20世纪80 年代以前,研究多基于农户层面的问卷调查展开,偏重对流转过程中农户流转行为,流转区位选择,流转与逆城市化带来的影响展开;国内学者对宅基地流转的关注日益提升,研究内容涉及流转中农户权益保障的政策讨论,农户心理与行为响应分析,农户需求与收益分配研究,流转政策实施评价等方面,研究以经济地理学、行为经济学、社会学等理论为指导,以探求农户需求与保障农户权益为出发点展开讨论,大量运用调查数据展开实证讨论。今后研究应加强对流转过程中各个主体需求的讨论,并注重对农户生存与经济、社会与精神等需求层面关注,加强地理空间信息与社会经济环境相结合的研究,加强对农户模型与计量经济学方法的系统运用与校验。