Semantic links in integrated modelling frameworks

The concept of sustainable development is now valued to be fundamental to most issues concerning human activities for development. As sustainable development requires balancing conflicting requirements, rational decision making is necessary to achieve sustainability. Simulation models to assess and forecast sustainability can aid rational decision making. In the context of human settlements, human-nature interactions need to be considered in an integrated manner to build appropriate simulation models. The integrated model framework proposed here serves as a base for such simulation models. The model framework is based on the premise that a community's attitude and its living environment determine human settlement sustainability. A generic model design comprising fundamental components of the proposed sustainability assessment and forecasting model framework is also presented in this paper. Discussion on relevant implementation issues including a simulation system and key limitations of the framework are also presented. This framework can be adopted for development and implementation of a simulation system for sustainability assessment and forecasting studies.

Ensuring consistent glycosylation-associated quality of therapeutic monoclonal antibodies (mAbs) has become a priority in pharmaceutical bioprocessing given that the distribution and composition of the carbohydrates (glycans) bound to these molecules determines their therapeutic efficacy and immunogenicity. However, the interaction between bioprocess conditions, cellular metabolism and the intracellular process of glycosylation remains to be fully understood. To gain further insight into these interactions, we present a novel integrated modelling platform that links dynamic variations in mAb glycosylation with cellular secretory capacity. Two alternative mechanistic representations of how mAb specific productivity (qp ) influences glycosylation are compared. In the first, mAb glycosylation is modulated by the linear velocity with which secretory cargo traverses the Golgi apparatus. In the second, glycosylation is influenced by variations in Golgi volume. Within our modelling framework, both mechanisms accurately reproduce experimentally-observed dynamic changes in mAb glycosylation. In addition, an optimisation-based strategy has been developed to estimate the concentration of glycosylation enzymes required to minimise mAb glycoform variability. Our results suggest that the availability of glycosylation machinery relative to cellular secretory capacity may play a crucial role in mAb glycosylation. In the future, the modelling framework presented here may aid in selecting and engineering cell lines that ensure consistent mAb glycosylatio.

ABSTRACTInundation dynamics in lowland rivers are an outcome of a complex interaction between hydrologic and geomorphic factors. The co‐occurrence of river flow and tidal surge in coastal regions further complicates these interactions. The extent to which these factors mediate inundation mechanisms in regulated lowland river reaches remains challenging and has been poorly understood. This study presents a novel framework that examines the combined effect of flood drivers (riverine and high tide) and geomorphic factors in determining the inundation mechanism along the Lower Tapi Basin (LTB) in western India through an integration of hydrological, tidal, hydrodynamic, and geomorphic datasets. Using variable infiltration capacity (VIC) and Hydrologic Engineering Center River Analysis System (2D HEC‐RAS) with geomorphic characteristics of river channels, we explore how spatial inundation dynamics vary across different valley settings under different flood return periods. Our integrated modelling framework accurately simulates daily streamflow and flood inundation. Incorporation of multidisciplinary data through the integrated modelling framework has advanced our understanding of flood inundation dynamics in lowland rivers. We have further shown that the model uncertainty can be reduced by incorporating field data, bathymetric measurements and rule curve of reservoir operation in the model domain. Although this modelling framework has been developed on a specific lowland reaches of the Tapi River, it can be further extended to any lowland rivers in similar settings. Such multidisciplinary models will help to analyse river response to future projected climate and sea level change.

近年来国内森林生态系统服务功能研究较多,但应用价值不高,其科学性受到诸多质疑。从森林水源涵养功能的多尺度内涵、过程以及其计量方法出发,对国内外研究动态和发展趋势进行了总结分析,重新审视森林水源涵养功能的研究意义,探讨森林水源涵养功能的多尺度特征。从森林水源涵养功能作用的空间尺度上看,其拦蓄洪水削减洪峰的功能仅在较小尺度上有效,而调节径流的功能只有当森林土壤的入渗量超过蒸散量时,才可能有更多地下水补给河道径流,进而增加旱季河道流量。同时森林水源涵养功能也具有明显的时间尺度特征,具体表现为在次降水事件中,由于蒸散发量较小,森林水源涵养功能的物质量等于森林不同层次的截留量,在功能上表现为拦蓄降水;在长时间尺度上,由于林地蒸散要耗去大量水分,森林水源涵养功能的物质量等于森林不同层次的截留量减去林地蒸散发量,在功能上表现为净化水质和调节径流。大多数研究仅对单一林分的个别层次蓄水功能进行研究,缺乏流域尺度或者更大空间尺度的森林水源涵养功能研究。建议从区域降尺度到流域或将坡面尺度上推到流域,集中在流域尺度解决森林水源涵养空间异质性将是解决森林水源涵养功能尺度外推的有效办法。就目前国内流行的森林水源涵养功能计量方法而言,其与尺度及研究目的有较大相关性,在研究中应根据研究目的、研究尺度和可获取的数据情况选择合适的计量方法。研究突出了不同尺度作用下森林水文过程的复杂性及重要性,并结合森林与水关系的争论问题,分析目前国内对森林水源涵养功能研究的一些误区,提出森林水源涵养功能研究的一些关键科学问题及未来可能的发展方向,主要包括:1)明确界定森林水源涵养功能的边界,探索森林水源涵养功能计量的新方法;2)加强不同时空尺度关联的森林水源涵养功能研究,包括正确评价森林水源涵养功能的时空变异规律,森林生态系统水源涵养功能的尺度效应,森林水源涵养与下游水生态安全,森林水源涵养研究范式转变等核心问题。;Forest water conservation as an important ecosystem function has caused a rising interests in the scientific community in recent years. However, there remain some arguments in several aspects regarding the forest water conservation function. For the concept of the forest water conservation, there is no clear definition about its connotation. Another concern is the scaling issue. It is a challenge to scale up the estimation for the forest water conservation from the plot scale to larger scale, e.g., watershed scale or regional scale. Many quantification methods have been developed, but their suitability, performance, advantages and disadvantages are unknown. Many of such argument issues are significant limits of the forest water conservation in science and management. On the basis of the literature review, we clarify the important role of the water conservation in forest ecosystem function. We also summarize and analyze the concepts of the forest water conservation and its multi-scale connotation, processes and quantification methods. On the spatial scale, function of the forest in mitigating peak flow is effective at a smaller scale but not necessarily at a larger scale. More groundwater recharges into stream flow when forest soil infiltration exceeds evapotranspiration, thus increasing stream flow in the dry season. During a rainfall event, forest water conservation has different features at different temporal scales. For example, the amount of the forest conservation during a rainfall event dominates by the forest canopy interception and most water is stored in the forest due to less evapotranspiration in the rainfall event scale. At the longer temporal scale, the forest water conservation can be determined by the forest canopy interception subtracting evapotranspiration. The functional roles of the forest water conservation at longer temporal scale dominate by purifying water from natural rainfall and mitigating seasonal flow peaks of the river discharges. Most previous studies of the forest water conservation focused on water storage function at the plot scale, but lack better understanding in the forest water conservation function at the watershed or regional scales. We suggest the approach that combines downscaling from the regional to watershed scales and upscaling from the hillside to the watershed scales can an effective way of the scale extrapolation. This idea can be used to address the heterogeneity issue of the forest water conservation function at different spatio-temporal scales. Among the existing quantification approaches of the forest water conservation function, each one highly relies on the temporal and spatial scales and its application goal. An appropriate calculation method should be carefully evaluated and considered based on the objectives, data availability, temporal and spatial scales of each study case. The suitability difference in different calculation methods of the forest water conservation demonstrates the complexity and importance of the multi-scale consideration in forest hydrological processes. In the context of the long-term debates about the relationship between the forest and water, we figure out a few confusing points in the current studies of the forest water conservation function. We also propose the critical scientific questions that should be addressed and a few directions in future studies of forest water conservation function including: 1) to clearly define the connotation and boundary of the forest water conservation function, and develop innovatory methods for determining the forest water conservation function; 2) to pay more attentions on the forest water conservation function studies associated with the different spatial and temporal scales, including evaluation of the spatio-temporal variations in forest water conservation function, the scaling effects on estimation of the water conservation function, the trade-off relationship between the upstream forest water conservation and the downstream ecological water need, and the development of the innovatory ways of forest water conservation practices.

This study uses an integrated modeling framework that couples the dynamics of hydrology, soil thermal regime, and ecosystem carbon and nitrogen to quantify the long‐term peat carbon accumulation in Alaska during the Holocene. Modeled hydrology, soil thermal regime, carbon pools and fluxes, and methane emissions are evaluated using observation data at several peatland sites in Minnesota, Alaska, and Canada. The model is then applied for a 10,000 year (15 ka to 5 ka; 1 ka = 1000 cal years before present) simulation at four peatland sites. We find that model simulations match the observed carbon accumulation rates at fen sites during the Holocene (R2 = 0.88, 0.87, 0.38, and −0.05 using comparisons in 500 year bins). The simulated (2.04 m) and observed peat depths (on average 1.98 m) were also compared well (R2 = 0.91). The early Holocene carbon accumulation rates, especially during the Holocene thermal maximum (HTM) (35.9 g C m− 2 yr− 1), are estimated up to 6 times higher than the rest of the Holocene (6.5 g C m− 2 yr− 1). Our analysis suggests that high summer temperature and the lengthened growing season resulted from the elevated insolation seasonality, along with wetter‐than‐before conditions might be major factors causing the rapid carbon accumulation in Alaska during the HTM. Our sensitivity tests indicate that, apart from climate, initial water table depth and vegetation canopy are major drivers to the estimated peat carbon accumulation. When the modeling framework is evaluated for various peatland types in the Arctic, it can quantify peatland carbon accumulation at regional scales.

Multi-level system modelling of the resource-food-bioenergy nexus in the global south

Spatially explicit land-use and land-cover scenarios for the Great Plains of the United States

Rapid urbanization has subjected the megacities of developing countries to various environmental stresses. Delhi, a major Indian megacity, faces increasing urban stress leading to reduction in air quality and visibility. These challenges necessitate an integrated modeling framework to mitigate adverse environmental impacts on public health. Therefore, we have developed an advanced version of the high-resolution Delhi Model with Chemistry and aerosol framework (DM-Chem) at the National Centre for Medium Range Weather Forecasting (NCMRWF) under the Weather and Climate Science for Service Partnership India (WCSSP India) project. This collaborative initiative between India and the United Kingdom aims to provide real-time forecasts of visibility and fine particulate matter (PM 2.5 ) for Delhi and neighboring regions during the winter season. The DM-Chem framework is unique due to its detailed urban canopy scheme and realistic aerosol representation, making it well suited for city-scale forecasts. It is designed to predict extreme fog and pollution events in the winter season. Here, we discuss the major physical parameterization improvements for the model, along with its skill and deficiencies in predicting extreme events. Notably, irrigation effects on surrounding agricultural areas have significantly improved fog and visibility forecasts, but have degraded the wind forecasts. We demonstrate the applicability of this modeling framework to study aerosol–radiation interaction during fog holes and discuss its potential to be applied or adapted to other megacities worldwide. Significance Statement The capital city Delhi and, in general, many metropolitan cities of India often report high levels of particulate matter pollution especially during wintertime, often accompanied by episodes of dense fog. Air quality and visibility forecasting for an urban region is dependent upon many key model inputs other than emissions and meteorology. Realistic representation of the (i) city’s local urban morphology, (ii) surface aerosols, and (iii) soil conditions impacted by irrigation activities has been found to significantly influence air quality and visibility prediction in Delhi and surrounding areas. This work aimed at providing a reliable air quality and visibility forecast for Delhi, which is crucial to minimize both health and economic losses.

ABSTRACTTwo modelling approaches are presented in this article for spatial and temporal analysis of water resources risk. Major sources of uncertainty in water resources management are spatial and temporal variability. Spatial variability occurs when values fluctuate with the location of an area and temporal variability occurs when values fluctuate with time. System dynamics (SD) simulation and hydrodynamic modelling are presented in this article as tools for modelling the dynamic characteristics of flood risk and its spatial variability. The first modelling framework presents SD simulation coupled with 3D fuzzy set theory. Whereas the second modelling framework presents hydrodynamic modelling coupled with 3D fuzzy set theory. The two integrated modelling frameworks are illustrated and compared using the Red River flood of 1997 (Manitoba, Canada) as a case study. For the 1997 Red River case study, SD simulation proved to be efficient modelling approach for capturing the feedback-based dynamic processes occurring in the watershed. However, the SD simulation has limited capacity for adequately representing spatial processes. The SD simulation coupled with 3D fuzzy set theory and geographic information system-based spatial analysis tool provides an integrated approach capable of modelling the spatial and temporal variability of flood risk. With respect to the topography of Red River basin, the hydrodynamic modelling coupled with 3D fuzzy set theory proved to be an accurate approach for predicting spatial and temporal variation of water surface elevation, velocity, flux, etc. The integrated approach demonstrates high accuracy in predicting spatial and temporal variability of flood risk.

This study focused on the structure of the aquatic insect community in spatial and temporal scales in the Esparza River. The river was sampled for one full year throughout 2007. During the dry season low flow months, five sampling points were selected in two different habitats (currents and pools), with five replicates per sample site. During the wet season with peak rain, only the data in the "current habitat" were sampled at each site. Specimens present in the different substrates were collected and preserved in situ. A nested ANOVA was then applied to the data to determine richness and density as the response variables. The variations in temporal and spatial scales were analyzed using width, depth and discharge of the river, and then analyzed using a nested ANOVA. Only a correlation of 51% similarity in richness was found, while in spatial scale, richness showed significant variation between sampling sites, but not between habitats. However, the temporal scale showed significant differences between habitats. Density showed differences between sites and habitats during the dry season in the spatial scale, while in the temporal scale significant variation was found between sampling sites. Width varied between habitats during the dry season, but not between sampling points. Depth showed differences between sampling sites and season. This work studies the importance of community structure of aquatic insects in rivers, and its relevance for the quality of water in rivers and streams.

Critical Zone Science (CZS) represents a powerful confluence of research agendas, tools, and techniques for examining the complex interactions between biotic and abiotic factors located at the interface of the Earth’s surface and shallow subsurface. Earth’s Critical Zone houses and sustains terrestrial life, and its interacting subsystems drive macroecological patterns and processes at a variety of spatial scales. Despite the analytical power of CZS to understand and characterize complicated rate-dependent processes, CZS has done less to capture the effects of disturbance and anthropogenic influences on Critical Zone processes, although some Critical Zone Observatories focus on disturbance and regeneration. Methodological approaches from biogeography and ecology show promise for providing Critical Zone researchers with tools for incorporating the effects of ecological and anthropogenic disturbance into fine-grained studies of important Earth processes. Similarly, mechanistic insights from CZS can inform biogeographical and ecological interpretations of pattern and process that operate over extensive spatial and temporal scales. In this paper, we illustrate the potential for productive nexus opportunities between CZS, biogeography, and ecology through use of an integrated model of energy and mass flow through various subsystems of the Earth’s Critical Zone. As human-induced effects on biotic and abiotic components of global ecosystems accelerate in the Anthropocene, we argue that the long temporal and broad spatial scales traditionally studied in biogeography can be constructively combined with the quantifiable processes of energy and mass transfer through the Critical Zone to answer pressing questions about future trajectories of land cover change, post-disturbance recovery, climate change impacts, and urban hydrology and ecology.

Healthy ecosystems such as forests and wetlands have a great potential to support adaptation to climate change and are the foundation of sustainable livelihoods. Ecosystem-based adaptation (EbA) can help to protect and maintain healthy ecosystems providing resilience against the impacts of climate change. This paper explores the role of EbA in reconciling socio-economic development with the conservation and restoration of nature in Lake Victoria Basin, Kenya, East Africa. Using selected ecosystems in the Lake region, the paper identifies key EbA approaches and explores trade-offs and synergies at spatial and temporal scales and between different stakeholders. The research methods used for this study include site visits, key informant interviews, focus group discussions, participatory workshops and literature reviews. An analytical framework is applied to advance the understanding of EbA approaches and how they lead to synergies and trade-offs between ecosystem services provision at spatial and temporal scales and multiple stakeholders. Our results show that EbA approaches such as ecosystem restoration have the potential to generate multiple adaptation benefits as well as synergies and trade-offs occurring at different temporal and spatial scales and affecting various stakeholder groups. Our paper underscores the need to identify EbA trade-offs and synergies and to explore the ways in which they are distributed in space and time and between different stakeholders to design better environmental and development programmes.

A whole-lake acoustic telemetry array was utilized to monitor the three-dimensional position of 20 largemouth bass (Micropterus salmoides). Code division multiple access (CDMA) technology enabled the simultaneous monitoring of the 20 transmitters (equipped with pressure and temperature sensors) at 15 s intervals with sub-meter accuracy. Fish were monitored between November 2003 and April 2004 to evaluate the behaviour of fish across different temporal and spatial scales. The distance moved by largemouth bass, assessed both on a daily and hourly basis, varied by season and was positively correlated with water temperature. For example, daily movement rates were 2.69 ± 1.45 km/day in mid November (average daily water temperature 5.9°C), 2.24 ± 0.73 km/day in early January (5.1°C), and 7.28 ± 2.62 km/day in mid April (7.7°C). Interestingly, daily movement rates varied by as much as 25 fold among individual fish. Visualization of fish swimming paths revealed that whereas some fish occupied discrete areas and made only localized movements, other individuals made lengthier journeys covering much of the lake in periods of as little as one day. Analysis of fish behaviour at a finer temporal scale revealed that during the winter, fish spend more than 95% of their time swimming at speeds less than 0.1 m/s (0.07 ± 0.24 m/s). During late fall, and especially in spring, swimming speeds were higher with mean swimming speeds of 0.11 ± 0.27 m/s and 0.19 ± 0.29 m/s, respectively. When the telemetry dataset was queried to simulate 24 h manual tracking intervals, it was clear that manual tracking data would not have been representative of actual daily movement rates, underestimating daily movement and swimming speeds by at least 75 fold. This study identifies the importance of evaluating fish activity at multiple spatial (whole lake to sub-meter position) and temporal (seasonal to seconds) scales and illustrates the potential of CDMA telemetry to yield such data.

<p>Agricultural use of pesticides helps control a range of pests and diseases that threaten crops, thereby avoiding yield losses and improving the quality of the food produced. However, pesticides applied on agricultural fields dissipate with time. The export of pesticides and their transformation products after application from the agricultural fields threatens the water quality of aquatic systems in many world regions.</p><p>Climate change is further expected to intensify pest pressures and potential pesticide use by affecting agriculture in many ways. Changing climatic conditions can increase pesticide leaching due to increased and frequent rainfall, higher degradation rates, or higher temperatures or soil moisture contents. The indirect effects are changes in land use, the timing of crop cultivation, selection of other crop types, new pests and changed pest behaviour, etc. Additionally, several socio-economic factors influence pesticide use at the farm and national level, including regulation and legislation, economy, technology and crop characteristics. In order to better understand the pesticide risk to surface waters in the future, we aim to understand the influence of both climate and socio-economic change on pesticide use and fate.</p><p>Various catchment-scale models are available to assess pesticides and their impacts on water bodies. However, most modelling approaches solely concentrate on the total amount or concentration of pesticide exported from a catchment and do not necessarily analyse the future change of pesticide and transformation products. We propose an integrated modelling framework to answer the research questions: What are the current significant climate and socio-economic drivers influencing pesticide use and emissions? How can climate change influence pesticide and transformation products emission trends? How will socio-economic change influence pesticide emissions?</p><p>The integrated modelling framework helps to include adapting agricultural production to climatic (e.g., temperature, precipitation) and socio-economic drivers (e.g., land use, crop type, pesticide regulation) and quantifying pesticide emissions with the Zin-AgriTRA pesticide fate model. The ZIN-AgriTra is a catchment scale reactive transport model which can simulate agrochemical and transformation products exported from agricultural catchments. We use the Eur-Agri-SSP scenarios that extend and enrich the basic Shared Socio-economic Pathways with a regional and sectoral component on agriculture to explain the socio-economic change and climate projections for Representative concentration pathways to adopt climate change scenarios.</p><p>The integrated modelling framework links the future scenario results from independent, standalone models that present crop rotation, land use, pesticide regulation and climate to the pesticide fate model (Zin-AgriTRA). The framework is applied to an agricultural catchment in Burgenland, Austria, to quantify pesticide pollution under future climate and socio-economic change up to 2050.</p><p> </p>

An integrated modeling framework – IMPACT – which integrates partial equilibrium economic model, hydrology model, crop simulation model and climate model was used to examine the ex-ante economic impact of developing and disseminating a drought tolerant sorghum cultivar in target countries of Africa and Asia. The impact of drought tolerant sorghum technology on production, consumption, trade flow and prices of sorghum in target and non-target countries were analyzed. And also we estimated the returns to research investment for developing the promising new drought tolerant cultivars and dissemination in the target countries. The analysis indicates that the economic benefits of drought tolerant sorghum cultivar adoption in the target countries outweighs the cost of developing this new technology. The development and release of this new technology in the target countries of Asia and Africa would provide a net economic benefit of about 1,476.8 million US$ for the entire world under no climate change condition. Under climate change scenarios the net benefits derived from adoption of new drought tolerant sorghum cultivar is higher than the no climate change condition. This is due to higher production realized by sorghum under climate change scenarios. The results imply that substantial economic benefits can be achieved from the development of a drought tolerant sorghum cultivar. And also this technology will perform better than the existing cultivars in future climate change condition.