Complexity and challenges of long-term environmental governance

Some important processes of environmental change – including those of climate change and loss of biodiversity – share three characteristics that make them extremely demanding challenges of governance. First, time-lags between human action and environmental effect are very long, often extending beyond one human generation. Second, problems are embedded in highly complex systems that are not well understood. Third, these problems involve global collective goods of a type that links them to a wide range of human activities and leaves them beyond the scope of unilateral solutions. Social science research offers two essentially different models of collective response to severe challenges. One portrays effective response as collective action through central leadership and contraction of power. The other conceives of societal response as involving a variety of local activities undertaken by subunits of a complex and decentralised system. I argue that both models have considerable merit, but also that they respond to different types of challenges. Therefore, useful insights can be gained by specifying more precisely the circumstances under which each model applies.     

Transfers and environmental co-benefits of carbon sequestration in agricultural soils: retiring agricultural land in the Upper Mississippi River Basin

This study investigates the carbon sequestration potential and co-benefits from policies aimed at retiring agricultural land in the Upper Mississippi River Basin, a large, heavily agricultural area. In addition to empirically measuring environmental co-benefits, we also compute economic transfers, which have sometimes been referred to as a co-benefit. Very little empirical work measuring the potential magnitude of these transfers has previously been undertaken. We compare and contrast alternative targeting schemes. We find that there are considerable amount of co-benefits and transfers and that the geographic distribution of co-benefits and transfers varies significantly with the specific benefit targeted. This implies that policy design related to targeting can have very important implications for both environmental conditions and income distributions in sub-regions. Issues related to policy design in the presence of co-benefits are considered. Senior authorship is shared equally between the first two authors. All views are those of the authors and not necessarily the funding agencies.     

A Review of Forest Gap Models

Forest gap models, initially conceived in 1969 as a special case of individual-tree based models, have become widely popular among forest ecologists for addressing a large number of applied research questions, including the impacts of global change on long-term dynamics of forest structure, biomass, and composition. However, they have been strongly criticized for a number of weaknesses inherent in the original model structure. In this paper, I review the fundamental assumptions underlying forest gap models, the structure of the parent model JABOWA, and examine these criticisms in the context of the many alternative formulations that have been developed over the past 30 years.Four assumptions originally underlie gap models: (1) The forest is abstracted as a composite of many small patches of land, where each can have a different age and successional stage; (2) patches are horizontally homogeneous, i.e., tree position within a patch is not considered; (3) the leaves of each tree are located in an indefinitely thin layer (disk) at the top of the stem; and (4) successional processes are described on each patch separately, i.e., there are no interactions between patches. These simplifications made it possible to consider mixed-species, mixed-age forests, which had been difficult previously mainly because of computing limitations.The structure of JABOWA is analysed in terms of the functional relationships used for formulating the processes of tree establishment, growth, and mortality. It is concluded that JABOWA contains a number of unrealistic assumptions that have not been questioned strongly to date. At the same time, some aspects of JABOWA that were criticized strongly in the past years are internally consistent given the objectives of this specific model.A wide variety of formulations for growth processes, establishment, and mortality factors have been developed in gap models over the past 30 years, and modern gap models include more robust parameterizations of environmental influences on tree growth and population dynamics as compared to JABOWA. Approaches taken in more recent models that led to the relaxation of one or several of the four basic assumptions are discussed. It is found that the original assumptions often have been replaced by alternatives; however, no systematic analysis of the behavioral effects of these conceptual changes has been attempted to date.The feasibility of including more physiological detail (instead of using relatively simple parameterizations) in forest gap models is discussed, and it is concluded that we often lack the data base to implement such approaches for more than a few commercially important tree species. Hence, it is important to find a compromise between using simplistic parameterizations and expanding gap models with physiology-based functions and parameters that are difficult to estimate. While the modeling of tree growth has received a lot of attention over the past years, much less effort has been spent on improving the formulations of tree establishment and mortality, although these processes are likely to be just as sensitive to global change as tree growth itself. Finally, model validation issues are discussed, and it is found that there is no single data source that can reliably be used for evaluating the behavior of forest gap models; instead, I propose a combination of sensitivity analyses, qualitative examinations of process formulations, and quantitative tests of gap models or selected submodels against various kinds of empirical data to evaluate the usefulness of these models for assessing their utility for predicting the impacts of global change on long-term forest dynamics.     

Walking with farmers: Floods,agriculture and the social practice of everyday mobility

Despite growing interest in the relationship between human mobility and environmental variability and change in recent years, there is relatively little understanding of the role of human agency within this nexus. This paper helps to address this knowledge gap by illuminating the role of perception, action and decision-making in the everyday. Using an innovative walking methodology, it presents an empirical case study of regularised farmers’ movements in and out of a floodplain during the rainy season in central Mozambique to show how people’s day-to-day routes are continuously reproduced through meaningful encounters and engagements with physical obstacles and other people. The paper demonstrates how a concern with everyday mobility highlights people’s day-to-day capacities to respond to environmental variability and change while also drawing attention to the challenges associated with the gradual accumulation of risk in mobile, rural livelihoods.     

A spatially explicit scenario-driven model of adaptive capacity to global change in Europe

Traditional impact models combine exposure in the form of scenarios and sensitivity in the form of parameters, providing potential impacts of global change as model outputs. However, adaptive capacity is rarely addressed in these models. This paper presents the first spatially explicit scenario-driven model of adaptive capacity, which can be combined with impact models to support quantitative vulnerability assessment. The adaptive capacity model is based on twelve socio-economic indicators, each of which is projected into the future using four global environmental change scenarios, and then aggregated into an adaptive capacity index in a stepwise approach using fuzzy set theory. The adaptive capacity model provides insight into broad patterns of adaptive capacity across Europe, the relative importance of the various determinants of adaptive capacity, and how adaptive capacity changes over time under different social and economic assumptions. As such it provides a context for the implementation of specific adaptation measures. This could improve integrated assessment models and could be extended to other regions. However, there is a clear need for a better theoretical understanding of the adaptive capacity concept, and its relationship to the actual implementation of adaptation measures. This requires more empirical research and coordinated meta-analyses across regions and economic sectors, and the development of bottom-up modelling techniques that can incorporate human decision making.     

Direct Nitrous Oxide Emissions Related to Fertilizer-Nitrogen,Precipitation, and Soil Clay Fraction: Empirical Models

Direct nitrous oxide(N2O) emissions(DNEs) from croplands are required in national inventories of greenhouse gases. The Intergovernmental Panel on Climate Change(IPCC) guidelines provide an approach using direct emission factors(EFds) to estimate DNEs, which are constants for large regions. The goal of this paper is to establish empirical models to account for the temporal and spatial variations of EFds, which, apart from the nitrogen addition rate, also vary with a range of environmental factors, so as to enhance the accuracy of regional/national DNE estimates. Therefore, the seasonal/annual DNEs(n = 71) from upland croplands, which are the differences in N2 O emissions between fields with and without fertilizer-nitrogen addition, were used to statistically relate DNEs to regulating factors including the fertilizer-nitrogen addition rate(FN), and environmental(climate and soil) factors. The multivariate stepwise linear regression results showed positive combined effects of FN and clay fraction on DNEs(R2 = 0.61, p 0.001). Furthermore, the nonlinear regression of FN, precipitation, and clay fraction was also adopted for prediction(R2 = 0.50, p 0.001). Validation with an independent dataset(n = 31) suggested that both models were better predictors of DNEs than the IPCC model, which only depends on FN. These empirical models may provide simple but reliable approaches for compiling regional/national, and even global inventories of DNEs from croplands. However, both models were restricted to a limited sample size. Understandably, more field observations are still required to further validate the global applicability of these simple approaches.     

土壤-植物-大气连续体（SPAC）系统中植物根系吸水模型研究进展

土壤植物系统是土壤-植物-大气连续体(SPAC)中的一个重要子系统。植物根系吸水过程是SPAC系统中水分运移规律研究的重要内容。从影响根系吸收土壤水分的影响因素人手，现有根系吸水模型可分为经验模型、半经验半理论模型和理论模型3类。文章综述了自20世纪60年代初第一个单根吸水模型以来的植物根系吸水模型及其最新研究进展，指出未来研究的重点是注重根系吸水机理同时，修改和完善已有根系吸水模型，简化模型参数，使之更易应用于实际。     

Snow pack in the Swiss Alps under changing climatic conditions: an empirical approach for climate impacts studies

Summary ?In many instances, snow cover and duration are a major controlling factor on a range of environmental systems in mountain regions. When assessing the impacts of climatic change on mountain ecosystems and river basins whose origin lie in the Alps, one of the key controls on such systems will reside in changes in snow amount and duration. At present, regional climate models or statistical downscaling techniques, which are the principal methods applied to the derivation of climatic variables in a future, changing climate, do not provide adequate information at the scales required for investigations in which snow is playing a major role. A study has thus been undertaken on the behavior of snow in the Swiss Alps, in particular the duration of the seasonal snow-pack, on the basis of observational data from a number of Swiss climatological stations. It is seen that there is a distinct link between snow-cover duration and height (i.e., temperature), and that this link has a specific “signature” according to the type of winter. Milder winters are associated with higher precipitation levels than colder winters, but with more solid precipitation at elevations exceeding 1,700–2,000 m above sea-level, and more liquid precipitation below. These results can be combined within a single diagram, linking winter minimum temperature, winter precipitation, and snow-cover duration. The resulting contour surfaces can then be used to assess the manner in which the length of the snow-season may change according to specified shifts in temperature and precipitation. While the technique is clearly empirical, it can be combined with regional climate model information to provide a useful estimate of the length of the snow season with snow cover, for various climate-impacts studies. Received May 14, 2002; revised August 12, 2002; accepted August 17, 2002     

Comparison of the performance of net radiation calculation models

Daily values of net radiation are used in many applications of crop-growth modeling and agricultural water management. Measurements of net radiation are not part of the routine measurement program at many weather stations and are commonly estimated based on other meteorological parameters. Daily values of net radiation were calculated using three net outgoing long-wave radiation models and compared to measured values. Four meteorological datasets representing two climate regimes, a sub-humid, high-latitude environment and a semi-arid mid-latitude environment, were used to test the models. The long-wave radiation models included a physically based model, an empirical model from the literature, and a new empirical model. Both empirical models used only solar radiation as required for meteorological input. The long-wave radiation models were used with model calibration coefficients from the literature and with locally calibrated ones. A measured, average albedo value of 0.25 was used at the high-latitude sites. A fixed albedo value of 0.25 resulted in less bias and scatter at the mid-latitude sites compared to other albedo values. When used with model coefficients calibrated locally or developed for specific climate regimes, the predictions of the physically based model had slightly lower bias and scatter than the empirical models. When used with their original model coefficients, the physically based model had a higher bias than the measurement error of the net radiation instruments used. The performance of the empirical models was nearly identical at all sites. Since the empirical models were easier to use and simpler to calibrate than the physically based models, the results indicate that the empirical models can be used as a good substitute for the physically based ones when available meteorological input data is limited. Model predictions were found to have a higher bias and scatter when using summed calculated hourly time steps compared to using daily input data.     

Luminous efficacy of global solar radiation on a horizontal surface for overcast and intermediate skies

Summary  In the first part of this research two models for the luminous efficacy of global solar radiation on horizontal surfaces and overcast skies have been developed. The first of these models is developed using a method similar to that proposed by Littlefair (1988). The second model has been obtained from the corresponding illuminance and irradiance models in an, apparently, new approach to the subject. In the second part of this research, a model for the luminous efficacy of global solar radiation for intermediate skies and horizontal surfaces is developed from the corresponding illuminance and irradiance models. The model for intermediate skies is given by the same mathematical function as that of the analogous model for overcast skies, and only the empirical constants change. In all the cases the only independent variables used are the solar altitude and the brightness index. The models proposed in the present paper have been statistically tested, and their prediction accuracy compared with other models available in the scientific literature. Received June 26, 2000 Revised December 9, 2000     

Framing environmental change in Africa: cross-scale institutional constraints on progressing from rhetoric to action against vulnerability

The reconciliation of national development plans with global priority to mitigate environmental change remains an intractable policy controversy. In Africa, its resolution requires integrating local knowledge into impact assessments without compromising the scientific integrity of the assessment process. This requires better understanding of the communication pathways involved in progressing from frame construction to political action on various environmental issues. The impacts of environmental factors on human health are a common concern in Africa, and it is examined here as a platform for negotiating controversies surrounding the arrogation of global support for local assessments of vulnerability and mitigation. The study focused on the particularities of projected impacts of climate change, and specifically on considerations of the health sector within the context of multivalent international agreements to conduct and use environmental assessments. The analysis addresses limitations of cross-scale communication nodes that are embedded in boundary institutions such as the Country Study Program which is hosted by industrialized nations. The translation of rhetoric into action frames through dynamic vulnerability assessments and critical frame reflection can equally engage indigenous and aided capacity for adapting to environmental change.     

Impact of vortex-removal from environmental flow in cyclone track prediction using Lagrangian advection model

In the present study, a new approach is discussed to find out the residual steering flow from the high-resolution global Numerical Weather Prediction (NWP) model-forecasted wind fields, which have been used in the Lagrangian advection model to determine the track of tropical cyclones formed in the Indian Ocean. The Lagrangian advection model is newly developed model and conceptually closer to the dynamical models, which utilizes environmental steering flow and the effect due to earth’s rotation (the beta-effect) to determine the motion of cyclone. In this approach, the effect of environmental flow on the cyclone track is examined by removing the existing cyclone vortex from the steering flow which is determined by potential vorticity approach. A new approach based on vortex pattern matching has been used to identify the cyclone vortex and to remove it from the steering flow. The tracks of five tropical cyclones (viz., Nargis, Khai_Muk, Nisha, Aila and Phyan) which were formed in the North Indian basin during the period 2008–2009 have been generated by the Lagrangian advection model using the proposed scheme. The position errors were computed with respect to the Joint Typhoon Warning Center (JTWC) best track analysis positions and compared with that of without-vortex-removal scheme. The results show that the mean track errors for five cyclones are reduced by 6–35?% for 12–72?h forecast in case of vortex-removal scheme as compared to the without-vortex-removal scheme.     

Estimation of hourly values of downward atmospheric radiation under cloudless skies during day- and night-time conditions

Summary Several atmospheric radiation models have been developed which provide methods for evaluating the effective emissivity of the atmosphere. Most of these methods are derived for night-time data utilizing local empirical coefficients. There are several, however, which are thought to be more universal in their predictive ability and some of these were tested on a data set registered in Granada from 1983 to 1985, inclusive. The models evaluated in this study are the Brutsaert model, the Berdahl and Martin model and the method proposed by Idso; in the first two cases the original coefficients were used. All the equations showed a good behaviour for night-time data but consistently overestimated day-time measured radiation. These deviations are explained in terms of day-night differences in the effective emissivity regime due to the differing vertical structure of the atmosphere during day and night. An empirical correction term for these differences improves the estimates of these models. The Idso model with a reduction in its independent term provided the best adjustment. Nevertheless, the Berdahl and Martin model with the original coefficients and the day-night correction term provided good results too, deviations being within the experimental error, indicating the universality of its coefficients.With 2 Figures     

Toward integrated assessment of environmental change: air pollution health effects in the USA

We demonstrate a method for integrating environmental effects into a computable general equilibrium model. This is a critical step forward toward the development of improved integrated assessment models of environmental change. We apply the method to examine the economic consequences of air pollution on human health for the US for the period from 1970 to 2000. The pollutants include tropospheric ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, and particulate matter. We apply this method to the MIT Emissions Prediction and Policy Analysis (EPPA) model, a computable general equilibrium model of the economy that has been widely used to study climate change policy. The method makes use of traditional valuation studies, incorporating this information so that estimates of welfare change are consistent with welfare valuation of the consumption of market goods and services. We estimate the benefits of air pollution regulations in USA rose steadily from 1975 to 2000 from $50 billion to $400 billion (from 2.1% to 7.6% of market consumption). Our estimated benefits of regulation are somewhat lower than the original estimates made by the US Environmental Protection Agency, and we trace that result to our development of a stock model of pollutant exposure that predicts that the benefits from reduced chronic air pollution exposure will only be gradually realized. We also estimate the economic burden of uncontrolled levels of air pollution over that period. The uncertainties in these estimates are large which we show through simulations using 95% confidence limits on the epidemiological dose-response relationships     

Adaptation,adaptive capacity and vulnerability

This paper reviews the concept of adaptation of human communities to global changes, especially climate change, in the context of adaptive capacity and vulnerability. It focuses on scholarship that contributes to practical implementation of adaptations at the community scale. In numerous social science fields, adaptations are considered as responses to risks associated with the interaction of environmental hazards and human vulnerability or adaptive capacity. In the climate change field, adaptation analyses have been undertaken for several distinct purposes. Impact assessments assume adaptations to estimate damages to longer term climate scenarios with and without adjustments. Evaluations of specified adaptation options aim to identify preferred measures. Vulnerability indices seek to provide relative vulnerability scores for countries, regions or communities. The main purpose of participatory vulnerability assessments is to identify adaptation strategies that are feasible and practical in communities. The distinctive features of adaptation analyses with this purpose are outlined, and common elements of this approach are described. Practical adaptation initiatives tend to focus on risks that are already problematic, climate is considered together with other environmental and social stresses, and adaptations are mostly integrated or mainstreamed into other resource management, disaster preparedness and sustainable development programs.     

Study on conventional atmospheric dispersion models in china, america and canada

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中国稻田甲烷产生和排放研究 Ⅱ.模式研究和减排措施

主要介绍了近 2 0年来稻田甲烷排放的模式研究和排放量的估算以及减少稻田甲烷排放的措施。数值模式是估算稻田甲烷排放量的一条有效途径 ,模式的研究现在正处于发展阶段。介绍了几个主要的模型 ,既有物理过程模型也有经验模型。年排放量的估算范围为 6 79～ 4 1 4Tg ,随着技术的发展和大量实验的进行估算值的精度正得到不断的提高。减排措施是减少稻田甲烷排放的必要手段 ,但是目前的减排技术均处于研究阶段 ,应用还不成熟     

Evaluation of support vector machine for estimation of solar radiation from measured meteorological variables

Solar radiation is an essential and important variable to many models. However, it is measured at a very limited number of meteorological stations in the world. Developing method for accurate estimation of solar radiation from measured meteorological variables has been a focus and challenging task. This paper presents the method of solar radiation estimation using support vector machine (SVM). The main objective of this work is to examine the feasibility of SVM and explore its potential in solar radiation estimation. A total of 20 SVM models using different combinations of sunshine ratio, maximum and minimum air temperature, relative humidity, and atmospheric water vapor pressure as input attributes are explored using meteorological data at 15 stations in China. These models significantly outperform the empirical models with an average 14 % higher accuracy. When sunshine duration data are available, model SVM2 using sunshine ratio and air temperature range is proposed. It significantly outperforms the empirical models with an average 26 % higher accuracy. When sunshine duration data are not available, model SVM19 using maximum temperature, minimum temperature and atmospheric water vapor pressure is proposed. It significantly outperforms the temperature-based empirical models with an average of 18 % higher accuracy. The remarkable improvement indicates that the SVM method would be a promising alternative over traditional approaches for estimation of solar radiation at any locations.