Estimating the uncertainty of modeled carbon sequestration: The GreenCert™ system

The GreenCert? system was developed to help farm and ranch owners to quantify, standardize, pool and market CO₂ emissions offset (sequestration) credits derived from improved rangeland or cropland management. It combines a user-friendly interface with the CENTURY biogeochemical model, a GIS database of soil and climate parameters, and a Monte Carlo-based uncertainty estimation methodology. This paper focuses on uncertainty treatment, discussing sources of error, parameter distributions, and the Monte Carlo randomization approach, culminating in a sensitivity analysis of model parameters.Idealized crop and grazing scenarios were used to evaluate the uncertainty of modeled soil organic carbon stocks and stock changes stemming from variability in site and management parameters. Normalized sensitivity coefficients and an integrated index for relative sensitivity of the model to the ensemble of the tested variables indicate that environmental factors are the most important in determining the actual size of the soil carbon stock, but that management is a much more important determinant of short- to medium-term carbon fluxes. GreenCert? uses the patented C-LOCK^® approach to efficiently limit uncertainty in the most critical phase of the modelling process by maximizing the use of available management information, and quantifies the remaining uncertainty in an unbiased fashion using Monte Carlo parameter randomization.     

Generating generic response signals for scenario calculation of management effects on carbon sequestration in agriculture: approximation of main effects using CENTURY

In this study, a well bounded and validated biogeochemical model, CENTURY, is used to mimic behaviour of soil carbon under different agricultural management regimes in Australian conditions to provide simple soil carbon response signals for use in a multi-criteria, spatial framework for analysis of management effects on carbon storage. The study is concerned with relative change in soil carbon resulting from change in management, and not concerned with absolute values either of change or final stock. Simulations were run for a range of starting soil carbon levels, soil physical properties, and climate sites using two carbon pool allocations within the model. A simplified set of agricultural land management options was used consisting of warm season native grassland, warm/cool season mixed native grassland, improved pasture, continuous wheat, conservation tillage, and long and short cereal rotations with lucerne. There were large differences in simulation results between crop and pasture systems and management types within systems. Within management types, starting soil carbon levels had the major influence on simulation outcomes. The derived carbon response signals for agricultural management practices, summarised over soils and climate, tended to underestimate losses under cropping and overestimate gains from perennial grassland when compared to field data. The value of these signals in a scenario analysis is discussed.     

Multitemporal Landsat TM imagery analysis for mapping and quantifying degraded rangeland in the Bahurutshe communal grazing lands,South Africa

Multitemporal remote sensing was used to map and quantify rangeland degradation in communal grazing lands of Lehurutshe district, northwestern South Africa. Based on established theory that veldt degradation ultimately results in bare land in addition to loss and replacement of palatable rangeland species, rangeland bare land was used as an indicator of degradation, primarily due to lack of palatable rangeland species spectral signatures. Using a January 1989 image as the base year, in which the rangelands were healthier, January 1995 and 2005 Landsat Thematic Mapper (TM) images were used for mapping and quantifying degradation, with the hypothesized degradation status that bare land in the rangelands would not have emerging grass just after the start of the summer rains. Image processing involved geometric registration, hybrid classification and geographic information system (GIS) overlay analysis. The results indicate moderate rangeland degradation, up to 4% area, particularly in the district's more inhabited south. Although the amount of degradation is moderate, the degradation has significant localized effects in this semiarid environment. Remote sensing techniques appear vital for rapid rangeland and other multitemporal spatial analyses in the area and the southern Africa subregion in general, to be taken advantage of with the launch of South Africa's environmental satellite.     

Testing the capabilities of the new WorldView-3 space-borne sensor’s red-edge spectral band in discriminating and mapping complex grassland management treatments

The majority of grasslands are overused and poorly managed, globally. The overuse of these grasslands has resulted in the adoption of numerous management treatments as interventions for optimizing their productivity. However, there are limited comprehensive frameworks and objective precedents for monitoring these grasslands and rangelands. In that regard, understanding the effect of such rangeland management treatments on grassland productivity is, therefore, a critical step towards their effective conservation and sustainable management. This study sought to test the capabilities of the WorldView-3 (WV-3) satellite data derivatives in characterizing grasslands administered with different rangeland management treatments (i.e. mowing, grazing, burning, fertilizer application, and control: no-treatment), using discriminant analysis. We compared the accuracies obtained based on WV-3 standard visible and near-infrared bands and vegetation indices (VIs), excluding and including the red-edge. Results illustrate that incorporating the strategically positioned red-edge band improves the classification accuracy of the four different rangeland management treatments from 65% to 70%. Furthermore, the overall accuracy was 73% when standard VIs were used and it increased to 78% when the red-edge VIs were added to standard VIs. Other than the red-edge derivatives, the results of this study showed that the yellow, red, NIR-1, and NIR-2 bands were the most influential. The utility of fine spatial resolution sensors such as the newly launched WV-3, with strategically positioned bands (red-edge), could offer detailed information essential for the sustainable management of grasslands.     

Climate simulations and projections with a super-parameterized climate model

The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in the simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. The climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.     

Trend analysis of Landsat-TM and -ETM+ imagery to monitor grazing impact in a rangeland ecosystem in Northern Greece

Mediterranean rangelands are unique marginal ecosystems, which are characterized by a highly heterogeneous structure and are often interwoven with other ecosystems. Traditionally, rangelands provided resources for livestock grazing in transhumantic rotation schemes. In recent times, there has been a trend towards semi-intensive grazing systems, which is partly connected to the European system of agricultural and infrastructural subsidies, and which effectuates both intensification and extensification. This study employed trend analysis of a remote sensing data time series for a retrospective assessment of rangeland processes, and interpreted these in the light of land-use practices and previous management interventions.We have selected a test area in Northern Greece that is representative of typical land-use transitions of the European Mediterranean. A time series of Landsat TM and ETM+ data covering the years 1984-2000 with one image per year was acquired, and for all images a geometric correction including digital elevation information and full radiative transfer modelling were carried out to attain surface reflectance data. For further analyses, proportional vegetation cover was selected as the target indicator, which was derived using Spectral Mixture Analysis. The resulting data set was used in a linear trend analysis to characterize spatio-temporal patterns of vegetation cover development. These could be interpreted based on knowledge of the local grazing regime and factors driving it, as well as using auxiliary spatial data sets. Results showed that temporal trends in the test area reflect the underlying pattern of potential livestock distribution at the per-pixel level, with a spatially differentiated pattern of both positive and negative trends in close proximity. On the other hand, no direct relation could be established between the development of vegetation cover and animal stocking rates at the community level. This suggests that this aggregation level is too coarse given the combination of highly heterogeneous landscapes with semi-intensive to intensive land tenure systems.     

Do intentions indicate actual behaviour? A comparison between scenario‐based experiments and real‐time observations of warning response

The sharp increase in the use of smartphones and rapid advances in mobile communication offer new ways to warn the public about developing natural or technological hazards. So far, the effectiveness of different warning types, namely standard and impact‐based warnings (SW and IBW), were mainly tested in scenario‐based experiments and not in real life. However, it can be questioned whether scenario‐based experiments are the appropriate methodology to test different warnings, for instance due to the absence of feelings catalysed by real events. Therefore, we collected information about warning responses in real time via the smartphone application ‘Wetter‐Alarm’ of a Swiss weather provider. In the first phase of the study, we conducted a field experiment to investigate actual responses for SW and IBW. In the second phase, we compared these results with behavioural intentions collected via a scenario‐based experiment with an almost identical set‐up. The comparison shows that warning messages were perceived and understood very similar in both experiments. Also, we did not observe any significant interactions between warning type (SW vs. IBW) and study (field vs. scenario‐based experiment). These findings indicate that the effects of warning type on behaviour can be studied on the basis of experimental (i.e. scenario‐based) research designs. The paper ends with some reflections on the potential of big data in the social sciences and on a research agenda for real‐time data collection to improve warning effectiveness and, ultimately, climate risk management.     

Assessing the propagation of uncertainties in multi-objective optimization for agro-ecosystem adaptation to climate change

It is widely acknowledged that uncertainty needs to be accounted for in climate impact studies, be it in scenario analyses or optimization applications. In this study we investigate how climate and crop model uncertainties affect multi-objective optimization outputs aiming to identify optimum agricultural management adaptations for Western Switzerland. Results are visualized by ternary plots that map optimum management measures, crop yield, erosion and leaching with associated uncertainties for navigating through the optimum adaptation space. We find that the relevance of climate model vs. parameter uncertainty can differ substantially depending on the prioritization of objectives and local conditions. The optimum choice of irrigation level was found to be the decision variable subject to greatest uncertainty particularly on coarser soil. This finding suggests that for the long-term planning of irrigation infrastructure and management, a robust adaptation approach is required for approaching unavoidable uncertainty from a risk management perspective.     

The urban heat island Mitigation Impact Screening Tool (MIST)

A web-based software tool has been developed to assist urban planners and air quality management officials in assessing the potential of urban heat island mitigation strategies to affect the urban climate, air quality, and energy consumption within their cities. The user of the tool can select from over 170 US cities for which to conduct the analysis, and can specify city-wide changes in surface reflectivity and/or vegetative cover. The Mitigation Impact Screening Tool (MIST) then extrapolates results from a suite of simulations for 20 cities to estimate air temperature changes associated with the specified changes in surface characteristics for the selected city. Alternatively the user can simply define a nominal air temperature reduction that they hope to achieve with an unspecified mitigation scenario. These air temperature changes are then input to energy and ozone models to estimate the impact that the mitigation action may have on the selected city. The results presented by MIST include a high degree of uncertainty and are intended only as a first-order estimate that urban planners can use to assess the viability of heat island mitigation strategies for their cities. As appropriate, MIST analyses should be supplemented by more detailed modeling.     

Phenology and carbon fixing: a satellite-based study over Continental USA

Global climate change has led to concerns about its impact on our biosphere and vegetation. Any impact of climate on vegetation can manifest in terms of changes in plant growth characteristics, its health and timing of different vegetative phenomena, such as germination, bud burst, maturity, etc. The duration and changes in the timing of plant growth stages can in turn impact the global carbon cycle. Similarly any change in plant productivity, because of changing climate will alter the carbon flux pattern by changing the overall biological flux being added or taken away from the atmosphere. We have used satellite data to study spatiotemporal changes in the plant phenology and plant productivity over the Continental USA (CONUS) to get an overall understanding of the evolution of these metrics over the past decade. Our study reveals that the prairies situated in the heartland of CONUS have become an increasingly important player in determining any changes in vegetation induced carbon source/sink patterns. The northern Great Plains has shown increased fixation of carbon in recent years, while the southern Plains has become a carbon source. This has been largely driven by changes in recent weather patterns where the northern plains have seen an increasingly cooler and wetter growing season whereas the southern plains have at the same time seen increased aridity, especially since 2011. This is also reflected in increasing growing season greenness values over the northern Plains and the opposite over the southern Plains. The gradual changing pattern of land biological fluxes over CONUS, as documented in this paper will likely be of interest to climate modellers as they seek to better understand the interaction between global carbon balance and climate change.     

Interaction Unit Analysis: A New Interaction Design Framework

ABSTRACT

A pragmatic approach to interaction modeling is presented by which a designer can describe how the user gets tasks done with a newly developing system. The notation proposed allows an interaction designer to make explicit both how user actions cause visible or noticeable changes in the state of the machine and how the user is expected to use this feedback to generate the next action. Interaction Unit (IU) scenarios are constructed where each IU specifies one step in the cycle of interaction. Each IU specifies the visible system state that leads the user to take some action. In addition, the IU makes explicit the state of the goal stack at the start and end of the unit and the mental processes (recall, recognition, or affordance) required. In this way one can describe the intimate connection between goal, action, and the environment in user–machine interaction.

To demonstrate the completeness of IU scenario analysis, IU models are presented for some well-known problems in interaction design: hidden and partially hidden modes leading to unexpected system effects, insufficient cues for subgoal construction, insufficient cues for subgoal elimination, and inappropriate affordances for action. These scenarios are accompanied by procedures that designers can use to detect similar problems in putative interaction designs.

To demonstrate the feasibility of using IU scenario analysis in design, 4 graduate students were taught to use IU scenario analysis in a 3-hr session. They then worked as a group to evaluate a prototype handheld warehouse application. A comparable group was taught and then applied Cognitive Walkthrough. Both groups successfully completed the task and detected several problems rated as being of high severity by the designers of the prototype. Analysis of the problems detected by each group suggests that the two techniques are complimentary. IU scenario analysis may be most cost-effective for devices using new interaction paradigms, whereas Cognitive Walkthrough may be most cost-effective for designs using established interaction paradigms.     

Impact of climate model uncertainties on socioeconomics: A case study with a medium mitigation scenario

Carbon dioxide (CO₂) emissions are strongly associated with economy. The amount of CO₂ that human society can emit in order to achieve a climate target depends on physical and biogeochemical properties in the climate system; these vary among climate models or earth system models (ESMs). Thus, uncertainties in such models, the spread remained when we both consider the range of existing models and observational data for key variables, can affect analysis of future global economy. In this study, using a computable general equilibrium model, we analyze the impacts on socioeconomics under a medium climate mitigation scenario by following three emission pathways considering uncertainties in existing ESMs (the lower and upper bounds as well as the mean). The results indicate that the impacts are larger in the lower bound case, despite the fact that economic and energy demands will increase continuously. In a comparison between the upper and lower bound cases, the carbon price of the latter case is approximately three times higher than that of the former case in 2100. Consequently, primary/final energy demand in the lower bound case becomes 1.0%/14% lower, and more renewables and carbon capture and storage are required to be used. Furthermore, the gross domestic product in the lower bound case is 4.1% smaller. Thus, within the scenario, the socioeconomic impacts caused by ESM uncertainties are not insignificant, but are smaller than the differences in annual and cumulative emissions.     

计及碳流的工业企业能源系统运行策略分析

为实现对工业企业能源系统中碳流轨迹的精确追踪,并制定有效的降碳运行策略,本文采用考虑网损的极坐标下的牛顿—拉夫逊迭代法,建立潮流稳态模型,用于分析系统中各节点和支路的有功潮流状态,以及网络损耗对系统性能的影响。此外,通过回归分析法对历史能耗数据进行建模,确定了燃煤发电机组的碳排放强度向量。进一步,建立了一个系统碳流分析模型,利用碳流与系统潮流的依赖关系,分析了各支路、负荷、以及网损的碳流率,以及各个节点的碳势。为了实证所提方法的有效性,采用IEEE 14节点系统为某工业企业构建了一个5机14节点的需求响应模型。通过仿真分析,研究了企业各用能环节的碳排放强度,实现了碳流的精确追踪。最后,为了优化工业企业能源系统的运行策略,采取了安装碳捕集装置和实施就地无功补偿两种措施,并通过模拟实验验证了这些措施降低系统碳排放的有效性。     

Inexact two-phase fuzzy programming and its application to municipal solid waste management

In this study, an inexact two-phase fuzzy programming approach was proposed for municipal solid waste management. Through introducing multiple control variables, objective function and constraints of the management model were relaxed under different levels, and compromised decision schemes with a high satisfactory level can be expected. Compared to the previous studies, it showed sound capability in identifying key factors and/or input conditions that may significantly affect system outputs, and thus facilitating the decision maker adjusting current system status to benefit the future management. A MSW management problem was provided to demonstrate the performance of the approach. Special parameters having significant or no impact on system performance were specified, which were then respectively changed to constitute two scenarios. The scenario analysis proved the accuracy of the model in identifying key factors. It was also found that the average satisfactory level of optimal solutions from the two-phase model was [0.287, 0.829], which was higher than that obtained from the conventional approach (i.e. [0.130, 0.804]), indicating the advantage of the proposed approach in searching for optimal solutions with high satisfactory level.     

东北植被生长峰值特征的变化及对气候和物候的响应

全球气候变化导致植被生长的季节性节律事件（如返青期、衰落期和生长峰值期等）发生显著变化。植被返青期、衰落期和生长季长度的变化已经得到广泛报道,植被生长峰值代表植被光合作用能力和对气候变化的响应,目前关于植被生长峰值特征（时间点和最大生长幅度）的时空变化和控制机理的研究相对较少,仍需在不同区域深入探讨。以植被覆盖度较好的中国东北地区为例,首先利用长时序遥感NDVI数据（GIMMS NDVI3g）和逻辑斯蒂法提取植被关键物候参数,然后分析了植被生长峰值关键特征（日期和幅度）的变化格局及对气候因子和返青期物候的响应,最后探索了生长峰值对植被生产力变化的贡献。结果表明：东北地区整体的生长峰值时间点和返青时间点呈现延迟趋势、生长幅度呈上升趋势（与MODIS EVI趋势验证一致）,生长峰值存在一个约11 a的周期;季前气温和降水对生长幅度的影响范围和幅度较小,主要作用在草原区域,对峰值时间点的显著影响主要在北部森林区域;返青期对生长峰值的控制作用大于气温和降水因素,并且返青期在森林和草原区域主要影响生长幅度变化,在农作物区主要影响生长峰值时间点变化;植被最大生长幅度对自然植被生产力长期变化的影响显著。东北地区生长峰值及对气候、物候响应的不同时空格局反映了植被生长峰值对气候变化的适应能力的差别,并造成多样的植被固碳格局。生长峰值研究有助于深入理解植被光合作用的时空变化格局和气候变化情景下的碳循环过程,对我国东北地区的生态系统评估和管理也有参考意义。     

Assessing rangeland degradation using multi temporal satellite images and grazing pressure surface model in Upper Mustang, Trans Himalaya, Nepal

This study aims to map and discriminate rangeland degradation from the effects of precipitation variability and thereby identify the driving forces of degradation in the grazing areas of Ghiling in Upper Mustang, Nepal. Landsat MSS, TM, ETM, and SPOT images covering the years 1976-2008 were analyzed. 8 km resolution NOAA NDVI from 1981to 2006 were used to identify the long term interrelationship between vegetation greenness and precipitation variability. The use of time series residual of the NDVI/precipitation linear regression to normalize the precipitation effect on vegetation productivity and identify the long term degradation was extended at the local scale. A weighted grazing pressure surface model was developed combining information from satellite images, topography, forage availability and detailed field work data on points of livestock concentration, herders' ranking of forage quality and grazing pattern in each pasture unit. The grazing pressure of a given site was defined as the product of annual net stocking density and the inverse of the total friction of livestock movement. While annual precipitation was found as the dominant factor for the interannual vegetation variability, degradation in Upper Mustang was the result of grazing induced change and some localized natural processes.     

Exploring Lake Victoria ecosystem functioning using the Atlantis modeling framework

Lake Victoria has experienced human induced pressures such as overfishing, introduction of alien species, increased eutrophication and climate change impacts. However, there is limited understanding of the system dynamics, major processes, drivers and responses to the changes. To address this challenge, we developed the first end-to-end whole ecosystem model (Atlantis) for the lake. The model is spatially resolved into 12 unique dynamic areas based on depth, species composition, physical-chemical characteristics and fisheries management zones. A total of 38 functional groups constitute the biological model. Four fishing fleets with different targeting options are simulated. Reliability of the model is confirmed by the good fit of simulations output to observational data sets. Herein, we describe the evolution of the biophysical system, illustrating how it responded to the aforementioned induced perturbations since 1958. The constructed virtual Lake Victoria ecosystem model provides a platform for exploring the impact of management interventions before actual implementation.     

Adapting grazing practices to limit the reforestation of mountainous summer pastures: A process-based approach

European mountain landscapes are experiencing massive land-use changes and high rates of natural reforestation since the 1950s. Summer pastures are particularly sensitive to those dynamics since their natural state depends on human activities. A process-based model - SHIELD (Simulating Herd Impact on Encroachment in upLanD) – has been developed to identify the key leverages of pastoral practices to limit the natural reforestation in the Haut-Vicdessos (Pyrenees Mountains, France). Simulations are compared to observed land cover changes to validate the model's structure. Scenarios are simulated to assess various grazing practices on reforestation dynamics: a baseline scenario and three scenarios with contrasted pastoral management: (i) reintroducing herds with no human supervision, (ii) reintroducing herds supervised by a shepherd and (iii) increasing the cattle load without supervision. Results show that supervising the intensity of land units' occupancy can be as efficient as increasing the cattle load to limit the ongoing trends of reforestation.     

Safety climate in trucking industry and its effects on safety outcomes

We developed a safety climate scale for the trucking industry and confirmed its criterion validity by correlations with safety outcome measures. A questionnaire survey was conducted to elicit safety climate in the trucking industry. A total of 1,028 responses (54 % response rate) were collected from truck drivers working for 49 trucking companies in Japan. Incident records between 2004 and 2008 were obtained from 21 out of the 49 companies that we surveyed safety climate. Following a factor extraction criteria (Horn’s parallel analysis), six factors on safety climate were elicited by applying principal component analysis with the Promax rotation, yielding 39 % of cumulative variance. Significant correlations with safety outcome measures were identified for the following safety climate factors: strong awareness of safety management/systems, teamwork, and realistic competence-based view. Safety climate contributes positively to the safety performance in a trucking organisation. Safety climate assessment using the factors developed in this paper is applicable as a proactive approach to risk reduction in the trucking industry.     

Do organizational citizenship behaviors lead to information system success?: Testing the mediation effects of integration climate and project management

We adapted a model in organizational theory to determine whether organizational citizenship behaviors (OCBs) of system implementation teams influenced that organization's integration climate and improved their project management, resulting in successful system implementation. Surveys were elicited from 254 system users in various business organizations that had implemented large-scale IS in the previous year; the analysis of their responses provided support for our model, suggesting that the OCB of the implementation team created a higher level of integration climate and more effective project management, and that these in turn influenced information system success. Implications for researchers and managers are discussed and limitations are identified.