Coupling a land use model and an ecosystem model for a crop-pasture zone

This paper describes the development of a land use model coupling ecosystem processes. For a given land use pattern in a region, a built-in regional ecosystem model (TESim) simulates leaf physiology of plants, carbon and nitrogen dynamics, and hydrological processes including runoff generation and run-on re-absorption, as well as runoff-induced soil erosion and carbon and nitrogen loss from ecosystems. The simulation results for a certain period from 1976 to 1999 were then used to support land use decisions and to assess the impacts of land use changes on environment. In the coupling model, the land use type for a land unit was determined by optimization of a weighted suitability derived from expert knowledge about the ecosystem state and site conditions. The model was applied to the temperate crop-pasture band in northern China (CCPB) to analyze the interactions between land use and major ecosystem processes and functions and to indicate the added value of the feedbacks by comparing simulations with and without the coupling and feedbacks between land use module and ecosystem processes. The results indicated that the current land use in CCPB is neither economical nor ecologically judicious. The scenario with feedbacks increased NPP by 46.78 g C m⁻² a⁻¹, or 32.23% of the scenario without feedbacks, also decreased soil erosion by 0.65 kg m⁻² a⁻¹, or 23.13%. Without altering the regional land use structure (proportions of each land use type). The system developed in this study potentially benefits both land managers and researchers.     

The effects of landscape-level disturbance on the composition of Minnesota caddisfly (Insecta: Trichoptera) trophic functional groups: evidence for ecosystem homogenization

Over 300,000 caddisfly specimens representing 249 species were collected from nearly 250 sites throughout Minnesota during 2000 and 2001 to determine the effects of human disturbance on the composition of caddisfly trophic functional groups at the landscape level. Canonical correspondence analysis determined that stream width was the most important variable influencing functional group composition in regions of the state with relatively low disturbance, and that differences in the caddisfly fauna between sizes of streams generally followed trends predicted by the river continuum concept. In regions of the state with moderate disturbance, both stream width and the percentage of disturbed habitat upstream of a site were important variables influencing functional group composition. In highly disturbed regions, no variables corresponded to changes in the composition of caddisfly functional groups. Instead, ecosystems were homogeneous: fine-particle filtering collectors dominated in all sizes of streams. The observed aquatic ecosystem homogenization is attributed mostly to input of fine-particle organic and inorganic sediment from extensive agriculture.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

基于第二次全国土地调查的云南省坝区县、半山半坝县和山区县的划分

云南是我国西部的典型山区省份,地形坡度<8°的坝区面积仅占土地总面积的6%左右。应用云南省第二次全国土地调查中对各县（市、区）≥1 km²坝子的调查和核定成果,选取坝区耕地面积比例、坝区土地面积比例、≥100 km²坝子数等3 个单项指标,并构建了综合指标--坝区土地综合指数,采用主导指标与综合分析相结合的方法,对全省129 个县（市、区） 进行坝区县、半山半坝县和山区县的划分。结果表明,全省有21 个县属于坝区县,37 个县属于半山半坝县,71 个县属于山区县。这一研究修订了以往云南省仅以坝区耕地面积比例为指标而划分出的坝区县、半山半坝县和山区县方案,为云南省及各地合理地进行产业布局（尤其是农业生产布局）、保护坝区优质耕地资源提供科学依据和基础支撑。     

澳大利亚新南威尔士州《污染土地管理法》及其实施效果

澳大利亚新南威尔士州1997年出台的《污染土地管理法》核心内容包括污染土地责任人的界定、初步调查令、重大污染土地的认定、治理令、自愿治理方案、继续治理令,以及污染土地治理费用的偿还,即环保署支付费用的偿还、公共权力机构执行命令时支付费用的偿还、当事人之间费用的偿还和统一基金拨款的偿还。《污染土地管理法》实施以来,效果较好。     

Fatal pedestrian crashes on interstates and other freeways in the United States

Introduction: More than 800 pedestrians die annually in crashes on interstates and other freeways in the United States, but few studies have examined their characteristics. Method: Data from the Fatality Analysis Reporting System on pedestrians fatally injured during 2015–2017 were analyzed. Chi-square tests compared characteristics of pedestrians killed on interstates and other freeways with those that died on other roads, and across crash types among freeway deaths. Land use characteristics of locations where pedestrians were killed while crossing freeways in a large state (California) were identified using Google Earth. Results: A larger proportion of pedestrians killed on freeways died on dark and unlit roads (48% vs. 32%), were male (78% vs. 68%), or were ages 20–44 (55% vs. 32%) compared with pedestrians killed on other roads. Crossing (42%) was the most common crash type among pedestrian deaths on freeways, followed by disabled-vehicle-related crashes (18%). Pedestrians who died while crossing more often had blood alcohol concentrations ≥ 0.08 g/dL (40%) than those in disabled-vehicle-related (22%) or other crashes (34%). Deaths in crossing crashes were more likely than other freeway deaths to occur on urban roads (81%), at speed limits ≤50 mph (13%), or between 18:00 and 23:59 (49%), and 58% of crossing crashes analyzed for land use were located between residential and other (e.g., commercial, recreational) uses. Over a third (37%) of deaths in disabled-vehicle-related crashes occurred at speed limits ≥70 mph. Conclusions: A surprising proportion of pedestrian deaths occur on controlled-access roads not designed for walking. Countermeasures for these crashes need to be implemented to see meaningful reductions in pedestrian fatalities overall. Practical applications: Improving roadway and vehicle lighting, requiring reflective warning devices for marking disabled vehicles, constructing pedestrian overpasses and underpasses in areas frequently crossed, and promoting alternative means of traveling between residential and commercial areas could help.     

Urbanisation-driven land degradation and socioeconomic challenges in peri-urban areas: Insights from Southern Europe

Climate change and landscape transformation have led to rapid expansion of peri-urban areas globally, representing new ‘laboratories’ for the study of human–nature relationships aiming at land degradation management. This paper contributes to the debate on human-driven land degradation processes by highlighting how natural and socioeconomic forces trigger soil depletion and environmental degradation in peri-urban areas. The aim was to classify and synthesise the interactions of urbanisation-driven factors with direct or indirect, on-site or off-site, and short-term or century-scale impacts on land degradation, focussing on Southern Europe as a paradigmatic case to address this issue. Assuming complex and multifaceted interactions among influencing factors, a relevant contribution to land degradation was shown to derive from socioeconomic drivers, the most important of which were population growth and urban sprawl. Viewing peri-urban areas as socio-environmental systems adapting to intense socioeconomic transformations, these factors were identified as forming complex environmental ‘syndromes’ driven by urbanisation. Based on this classification, we suggested three key measures to support future land management in Southern European peri-urban areas.     

Acid sulfate soils and human health—A Millennium Ecosystem Assessment

Acid sulfate soils have been described as the “nastiest soils on earth” because of their strong acidity, increased mobility of potentially toxic elements and limited bioavailability of nutrients. They only cover a small area of the world's total problem soils, but often have significant adverse effects on agriculture, aquaculture and the environment on a local scale. Their location often coincides with high population density areas along the coasts of many developing countries. As a result, their negative impacts on ecosystems can have serious implications to those least equipped for coping with the low crop yields and reduced water quality that can result from acid sulfate soil disturbance. The Millennium Ecosystem Assessment called on by the United Nations in 2000 emphasised the importance of ecosystems for human health and well-being. These include the service they provide as sources of food and water, through the control of pollution and disease, as well as for the cultural services ecosystems provide. While the problems related to agriculture, aquaculture and the environment have been the focus of many acid sulfate soil management efforts, the connection to human health has largely been ignored. This paper presents the potential health issues of acid sulfate soils, in relation to the ecosystem services identified in the Millennium Ecosystem Assessment. It is recognised that significant implications on food security and livelihood can result, as well as on community cohesiveness and the spread of vector-borne disease. However, the connection between these outcomes and acid sulfate soils is often not obvious and it is therefore argued that the impact of such soils on human well-being needs to be recognised in order to raise awareness among the public and decision makers, to in turn facilitate proper management and avoid potential human ill-health.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

Methodology of industry scale analysis under the constraint of regional resource capacity using HSY algorithm

This paper develops a methodology of proper scale analysis for regional industry development, which can be used in industry planning with the consideration of regional resource capacities. In the face of different data sources and even data scarcity, alternative methods based on linear programming and quadratic programming algorithms for calculating the resource intensity factors are designed. Based on the empirical study of industrialization, initial scenarios of industry development were set. Using HSY algorithm, sensitive industries that may cause exceeding regional resource capacity can be identified, and the risk of exceeding can be predicted and expressed in probability. Furthermore, a proper scale range can be designed for these sensitive industries according to resource capacity. Taking the case of Dalian city in China, this paper estimated the regional urban development plan, various resources capacities were studied, and land resources were estimated to be the most critical resource for the city. The land resource depletion intensities of different industries are calculated by quadratic programming algorithm. Under the constraint of 427.56 km² available industrial land resources, the electronic and power industries have the most significant impact on total land use, if the scale of power industry exceeds 1.27 billion USD, the probability of land resource capacity breakthrough will be 50%.