Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA

This paper presents an approach to modeling land-cover change as a function of land-use change. We argue that, in order to model the link between socio-economic change and changes in forest cover in a region that is experiencing residential and recreational development and agricultural abandonment, land-use and land-cover change need to be represented as separate processes. Forest-cover change is represented here using two transition probabilities that were calculated from Landsat imagery and that, taken together, describe a Markov transition matrix between forest and non-forest over a 10-year period. Using a three-date land-use data set, compiled and interpreted from digitized parcel boundaries, and scanned aerial photography for 136 sites (c. 2500 ha) sampled from the Upper Midwest, USA, we test functional relationships between forest-cover transition probabilities, standardized to represent changes over a decade, and land-use conditions and changes within sample sites. Regression models indicated that about 60% of the variation in the average forest-cover transition probabilities (i.e. from forest to non-forest and vice versa) can be predicted using three variables: amount of agricultural land use in a site; amount of developed land use; and the amount of area increasing in development. In further analysis, time lags were evaluated, showing that agricultural abandonment had a relatively strong time-lag effect but development did not. We demonstrate an approach to using forest-cover transition probabilities to develop spatially-constrained simulations of forest-cover change. Because the simulations are based on transition probabilities that are indexed to a particular time and place, the simulations are improved over previous applications of Markov transition models. This modeling approach can be used to predict forest-cover changes as a result of socio-economic change, by linking to models that predict land-use change on the basis of exogenous human-induced drivers.     

Transition Pathways to Sustainable Agricultural Water Management: A Review of Integrated Modeling Approaches

Agricultural water management (AWM) is an interdisciplinary concern, cutting across traditional domains such as agronomy, climatology, geology, economics, and sociology. Each of these disciplines has developed numerous process‐based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross‐disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM — the actual practice of conserving water while maximizing productivity. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

河西走廊绿色农业循环模式研究

以绿色农业理念为基础,针对河西走廊绿洲灌区环境资源特点、产业优势及生产中存在的问题,通过对当地玉米、小麦两大主栽作物秸秆饲料化利用、肉牛健康养殖、废弃物综合利用、农畜产品生产全程质量监控等技术的组装配套,研究总结形成种养结合、资源循环利用、清洁生产的绿色农业发展模式,即种养结合型模式＂玉米-牛-沼-肥＂、大田设施配套型模式＂小麦-菇-肥-果（葡萄）＂、小型养殖场型模式＂牛-沼/蚯蚓-肥/饲料＂,并对模式的原理、特点、技术集成要点及效益进行阐述分析。对该3种模式在武威市凉州区谢河镇示范验证,农田节水30%,秸秆养殖利用率达到60%,牛羊良种化率提高30%,奶牛母犊牛生产率达88%,减少化肥施用量20%,减少生活能源支出55%,减少农业废弃物排放75%,提高农业综合效益36%。     

Environmental sub models for a macroeconomic model: agricultural contribution to climate change and acidification in Denmark

Integrated modelling of the interaction between environmental pressure and economic development is a useful tool to evaluate environmental consequences of policy initiatives. However, the usefulness of such models is often restricted by the fact that these models only include a limited set of environmental impacts, which are often energy-related emissions. In order to evaluate the development in the overall environmental pressure correctly, these model systems must be extended. In this article an integrated macroeconomic model system of the Danish economy with environmental modules of energy related emissions is extended to include the agricultural contribution to climate change and acidification. Next to the energy sector, the agricultural sector is the most important contributor to these environmental themes and subsequently the extended model complex calculates more than 99% of the contribution to both climate change and acidification. Environmental sub-models are developed for agriculture-related emissions of CH(4), N(2)O and NH(3). Agricultural emission sources related to the production specific activity variables are mapped and emission dependent parameters are identified in order to calculate emission coefficients. The emission coefficients are linked to the economic activity variables of the Danish agricultural production. The model system is demonstrated by projections of agriculture-related emissions in Denmark under two alternative sets of assumptions: a baseline projection of the general economic development and a policy scenario for changes in the husbandry sector within the agricultural sector.     

Agricultural nitrogen model: A tool for regional environmental management

A detailed nitrogen budget was devised for agricultural activities in the Florida peninsula, based on routine data published by state agricultural agencies. The model demonstrates that important unmonitored fluxes of nitrogen can often be calculated by mass balance on individual model compartments, and that the reasonability of poorly quantified fluxes can be assessed. The results of such models can be very useful in designing and assessing the results of field experiments and in prioritizing environmental monitoring programs.     

荷兰生态（有机）农业对上海农业发展的借鉴

安全高效、资源节约、环境友好型的生态农业生产技术,已成为国际农业领域研究和关注的热点;发展高效生态（有机）农业,以新的强度和效能为长三角和我国现代化农业发展作贡献,是上海社会主义新农村建设的重大战略,是上海现代农业发展的必由之路。荷兰生态（有机）农业发展提供了以下成功经验：以生态学原理指导农业生产,实现生产生态共荣;在农产品生产中应用HACCP理论,加强农业生产的过程控制和质量管理;通过制定良好农业技术规范（Eurep-GAP）,保障农业的可持续发展,保护生态环境。上海发展高效生态（有机）农业的对策建议：加强政策扶持,深化有机农业理论和技术研究,建立和规范与国际接轨的认证体系,以生态学的原理和原则指导农业生产和技术的发展。     

Environmentally adjusted productivity measurement: an Australian case study

This paper critically examines various methods for estimating productivity incorporating environmental effects for the Australian agricultural sector. The agricultural sector has been selected because of its strategic position in the economy of Australia. The findings of this study indicate that the application of environmentally adjusted productivity methods is a credible approach to measure productivity, in the context of sustainable development. Although the empirical findings of this research are case study specific, the results provide evidence supporting the adoption of these techniques to other sectors of the economy when measuring productivity and needing to be cognisant of sustainable development. The findings suggest that adjusting for the environmental impacts of soil erosion can result in higher or lower agricultural productivity depending on the assumptions we make regarding damage costs of erosion. It is argued in this paper that, for soil erosion in Australia, assumptions yielding higher productivity (i.e., upwardly adjusted) are justified. Finally, the findings of this study and the use of the methods presented point to important gaps in data availability. This gap needs to be addressed by policy makers if sustainable development objectives are to be credibly assessed using these techniques.     

Little by little,inch by inch: Project expansion assessments in the Papua New Guinea mining industry

Social impact assessment (SIA) has traditionally been practiced as an ex-ante predictive tool in the context of regulatory approval by government agencies. This model of SIA developed by Burdge and others is based on ‘greenfields’ development, of a new project going in to areas where there are no, or relatively few, similar types of development. The International Principles of SIA signalled a conceptual shift in the practice of SIA where greater emphasis is placed on the assessment and management of social issues across the life-cycle of developments. In addition forms of cumulative impact assessment have been developed for contexts where more than one project is likely to impact on populations or communities. With these changes to the traditional models of impact assessment there is a need to clarify how and when dedicated phases of ‘assessment’ might be undertaken over the life-cycle of a development. In the context of the mining industry, SIAs are increasingly required by governments for incremental increases in the size or impact of these operations. This paper reviews the development and application of Project Expansion Assessments (PEAs) for two large-scale mining operations in Papua New Guinea. It argues that a different set of assumptions need to underlie the model of IA for such assessments, with more emphasis on trajectories rather than baselines, a critical evaluation and attribution of effects, and the incorporation of adaptive management tools into the process.     

NEW METHODS OF MODELING WATER AVAILABILITY FOR AGRICULTURE UNDER CLIMATE CHANGE: THE U.S. CORNBELT1

ABSTRACT: This paper reports on new methods of linking climate change scenarios with hydrologic, agricultural an water planning models to study future water availability for agriculture, an essential element of sustainability. The study is based on the integration of models of water supply and demand, and of crop growth and irrigation management. Consistent modeling assumptions, available databases, and scenario simulations are used to capture a range of possible future conditions. The linked models include WATBAL for water supply; CERES, SOYGRO, and CROPWAT for crop and irrigation modeling; and WEAP for water demand forecasting, planning and evaluation. These models are applied to the U.S. Cornbelt using forecasts of climate change, agricultural production, population and GDP growth. Results suggest that, at least in the near term, the relative abundance of water for agriculture can be maintained under climate change conditions. However, increased water demands from urban growth, increases in reservoir evaporation and increases in crop consumptive use must be accommodated by timely improvements in crop, irrigation and drainage technology, water management, and institutions. These improvements are likely to require substantial resources and expertise. In the highly irrigated basins of the region, irrigation demand greatly exceeds industrial and municipal demands. When improvements in irrigation efficiency are tested, these basins respond by reducing demand and lessening environmental stress with an improvement in system reliability, effects particularly evident under a high technology scenario. Rain-fed lands in the Cornbelt are not forced to invest in irrigation, but there is some concern about increased water-logging during the spring and consequent required increased investment in agricultural drainage. One major water region in the Cornbelt also provides a useful caveat: change will not necessarily be continuous and monotonic. Under one GCM scenario for the 2010s, the region shows a significant decrease in system reliability, while the scenario for the 2020s shows an increase.     

TurfPQ, a pesticide runoff model for turf

Environmental assessments of golf courses and other turf systems must often rely on mathematical modeling. However, in the case of pesticide runoff, successful modeling applications are rare. Available models were developed for agricultural applications and have seen very limited testing for turf. TurfPQ is a pesticide runoff model developed exclusively for turf. The model is based on a curve number calculation for runoff volume and linear partitioning of pesticide into adsorbed and dissolved components during a precipitation or irrigation event. Calibration is optional, so the model can be applied, using default parameter values, to situations where runoff and chemical loss data are unavailable. TurfPQ was tested with default parameter values for 52 pesticide runoff events involving six pesticides measured in plot studies in four states. The model typically produced conservative overpredictions of pesticide runoff, particularly with strongly adsorbed pesticides. Mean predicted pesticide runoff was 2.9% [corrected] of application, compared with an observed mean of 2.1%. TurfPQ captured the dynamics of the pesticide runoff events well with R2 = 0.65 [corrected]. Sensitivity analyses indicated that prediction errors could be reduced by better estimates of adsorption parameters and runoff curve numbers. However, even with default parameters, TurfPQ predictions are at least as accurate as those produced by more complex models.     

Trade-off analysis in the Northern Andes to study the dynamics in agricultural land use

In this paper we hypothesize that land use change can be induced by non-linearities and thresholds in production systems that impact farmers' decision making. Tradeoffs between environmental and economic indicators is a useful way to represent dynamic properties of agricultural systems. The Tradeoff Analysis (TOA) System is software designed to implement the integrated analysis of tradeoffs in agricultural systems. The TOA methodology is based on spatially explicit econometric simulation models linked to spatially referenced bio-physical simulation models to simulate land use and input decisions. The methodology has been applied for the potato-pasture production system in the Ecuadorian Andes. The land use change literature often describes non-linearity in land use change as a result of sudden changes in the political (e.g. new agricultural policies) or environmental setting (e.g. earthquakes). However, less attention has been paid to the non-linearities in production systems and their consequences for land use change. In this paper, we use the TOA system to study agricultural land use dynamics and to find the underlying processes for non-linearities. Results show that the sources of non-linearities are in the properties of bio-physical processes and in the decision making-process of farmers.     

Ethics,Narrative, and Agriculture: Transforming Agricultural Practice through Ecological Imagination

The environmental degradation caused by industrial agriculture, as well as the resulting social and health consequences, creates an urgency to rethink food production by expanding the moral imagination to include agricultural practices. Agricultural practices presume human use of the earth and acknowledge human dependence on the biotic community, and these relations mean that agriculture presents a separate set of considerations in the broader field of environmental ethics. Many scholars and activists have argued persuasively that we need new stories to rethink agricultural practice, however, the link—the story that does and can shape agricultural practice—has not yet been fully articulated in environmental discourse. My analysis explores how language has shaped existing agricultural models and, more important, the potential of story to influence agricultural practice. To do this, I draw upon cognitive theory to illustrate how metaphoric and narrative language structures thought and influences practice, beginning with my contention that industrial agriculture relies on a discourse of mechanistic relations between humans and a passive earth, language that has naturalized the chemically intensive monocultures prevalent in much of the American Midwest. However, alternative agricultures, including organic agriculture, agro-ecology, and ecological agriculture, emphasize qualities such as interdependence and reciprocity and do so as a deliberate response to the perceived inadequacies of industrial agriculture and its governing narrative. Exploring the different discourses of agricultural systems can help us think through different modalities for human relations with the biotic community and demonstrate story’s potential role in altering practice.     

Can market-based policies accomplish the optimal floodplain management? A gap between static and dynamic models

The purpose of this short article is to set static and dynamic models for optimal floodplain management and to compare policy implications from the models. River floodplains are important multiple resources in that they provide various ecosystem services. It is fundamentally significant to consider environmental externalities that accrue from ecosystem services of natural floodplains. There is an interesting gap between static and dynamic models about policy implications for floodplain management, although they are based on the same assumptions. Essentially, we can derive the same optimal conditions, which imply that the marginal benefits must equal the sum of the marginal costs and the social external costs related to ecosystem services. Thus, we have to internalise the external costs by market-based policies. In this respect, market-based policies seem to be effective in a static model. However, they are not sufficient in the context of a dynamic model because the optimal steady state turns out to be unstable. Based on a dynamic model, we need more coercive regulation policies.     

Energy Supply Potentials and Needs, and the Environmental Impact of their Use in Sudan

Sudan is an agricultural country with fertile land, plenty of water resources, livestock, forestry resources, and agricultural residues. An overview of the energy situation in Sudan is introduced with reference to the end uses and regional distribution. Energy sources are divided into two main types; conventional energy (biomass, petroleum products, and electricity); and non-conventional energy (solar, wind, hydro-electricity, etc.). Sudan possesses a relatively high abundance of solar radiation, and moderate wind speeds, hydro, and biomass energy resources. The application of the new and renewable sources of energy available in Sudan is now a major issue in future energy strategic planning and for an alternative to fossil conventional energy. Sudan is an important case study in the context of renewable energy. It has a long history of meeting its energy needs through renewables. Sudan's renewables' portfolio is broad and diverse, due in part to the country's wide range of climates and landscapes. Like many of the African leaders in renewable energy utilization, Sudan has a well-defined commitment to continue research, development, and implementation of new technologies. Sustainable low-carbon energy scenarios for the new century emphasize the untapped potential of renewable resources. Rural areas of Sudan can benefit from this transition. The increased availability of reliable and efficient energy services stimulates new development alternatives. It is concluded that renewable, environmentally friendly, energy must be encouraged, promoted, invested, implemented, and demonstrated by full-scale plants, especially for use in the remote rural areas of Sudan.     

Development and Climate Change: A Mainstreaming Approach for Assessing Economic,Social, and Environmental Impacts of Adaptation Measures

The paper introduces the so-called climate change mainstreaming approach, where vulnerability and adaptation measures are assessed in the context of general development policy objectives. The approach is based on the application of a limited set of indicators. These indicators are selected as representatives of focal development policy objectives, and a stepwise approach for addressing climate change impacts, development linkages, and the economic, social and environmental dimensions related to vulnerability and adaptation are introduced. Within this context it is illustrated using three case studies how development policy indicators in practice can be used to assess climate change impacts and adaptation measures based on three case studies, namely a road project in flood prone areas of Mozambique, rainwater harvesting in the agricultural sector in Tanzania and malaria protection in Tanzania. The conclusions of the paper confirm that climate risks can be reduced at relatively low costs, but the uncertainty is still remaining about some of the wider development impacts of implementing climate change adaptation measures.     

ASSESSMENT OF REMOTE SENSING INPUT TO HYDROLOGIC MODELS1

Remotely sensed variables such as land cover type and snow-cover extent can currently be used directly and effectively in a few specific hydrologic models. Regression models can also be developed using physiographic and snow-cover data to permit estimation of discharge characteristics over extended periods such as a season or year. Most models, however, are not of an appropriate design to readily accept as input the various types of remote sensing parameters that can be obtained now or in the future. Because this new technology has the potential for producing hydrologic data that has significant information content on an areal basis, both inexpensively and repetitively, effort should be devoted now to either modifying existing models or developing new models that can use these data. Minor modifications would at least allow the remote sensing data to be used in an ancillary way to update the model state variables, whereas major structural modifications or new models would permit direct input of the data through remote sensing compatible algorithms. Although current remote sensing inputs to hydrologic models employ only visible and near infrared data, model modification or development should accommodate microwave and thermal infrared data that will be more widely available in the future.     

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.     

农村商品流通网络模型及其发展趋势

农村商品流通是影响农业发展和农民消费的直接因素，完善农村商品流通网络对开拓农村市场，增加农民收入，发展农村经济具有推动作用。首先论述了农村商品流通网络的内涵；其次提出了基于主导要素的3种农村商品流通网络模型，即交易市场主导型、企业组织主导型和流通技术主导型，并对网络主体及其关系等方面进行了分析；最后提出了农村商品流通网络的发展趋势及其相应对策。     

Are there limits to growth? The need for a transition to a solar-based economy

The idea of limits to growth has, understandably, achieved notoriety since the days of Malthus and, more recently, the Club of Rome. However, there must be some limits to the ability of the earth to sustain a growing population. Fortunately, population models suggest that the world's population will probably level out at about two to three times the present numbers over the next hundred years. The question is whether the earth's resources are sufficient to sustain that population at a high standard of living for all. In this the key issue is energy. It is clear that present trends in energy consumption, especially oil, cannot be sustained much longer. Regardless of this, however, prudence demands a drastic reduction in fossil fuel consumption, in view of the possibility of global warming. It can be shown that, combined with greatly improved energy efficiency, a transition to a solar (renewable) energy based economy, capable of sustaining the anticipated growth in the world economy, is possible, but the constraints are extremely tight .