The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic ...models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches.
•Extreme events and future climate uncertainty represent risk for food production.•Crop models are largely able to simulate crop response to climate factors.•Adaptations are best evaluated in integrated assessment models (IAM).•Key limitations for crop models in IAM are low data availability and integration.•Cross-scale nature of IAM suggests novel modelling approaches are needed.
•Links between soil properties and profile imagery investigated for Ethiopian soils.•Explored the using a smartphone to estimate soil properties in the field.•Neural network and Partial Least Squares ...models were explored.•Models used soil colour and spatial covariates derived from site location.•Accuracy was consistently higher using colour and spatial covariate data together.
The links between soil properties and smartphone imagery were investigated for 273 samples in the Halaba area of south-west Ethiopia. The aim of this was to explore the possibility of using a smartphone-based system to estimate soil properties in the field, without the need for sampling and laboratory analysis. This presents an opportunity to develop low cost soil assessment in remote locations. Imagery and associated site characteristics were captured using an ODK (Open Data Kit) interface developed specifically for the project. Two types of model linking image information to soil properties were explored, backpropagation neural networks (NN) and partial least squares (PLS). Models were generated with colour alone, spatial covariates alone and a combination of colour and spatial covariates. Two sets of data, for soil chemistry and soil physical properties, were modelled. For both NN and PLS models, estimation accuracy for chemical properties was consistently higher using colour and spatial covariate information together rather than colour or spatial covariates alone. For physical properties a similar pattern was seen but this was less clear, and estimation of physical properties was less successful based on statistical model validation.
Five stakeholder-relevant indices of agro-meteorological change were analysed for the UK, over past (1961–1990) and future (2061–2090) periods. Accumulated Frosts, Dry Days, Growing Season Length, ...Plant Heat Stress and Start of Field Operations were calculated from the E-Obs (European Observational) and HadRM3 (Hadley Regional Climate Model) PPE (perturbed physics ensemble) data sets. Indices were compared directly and examined for current and future uncertainty. Biases are quantified in terms of ensemble member climate sensitivity and regional aggregation. Maps of spatial change then provide an appropriate metric for end-users both in terms of their requirements and statistical robustness. A future UK is described with fewer frosts, fewer years with a large number of frosts, an earlier start to field operations (e.g., tillage), fewer occurrences of sporadic rainfall, more instances of high temperatures (in both the mean and upper range), and a much longer growing season.
The intention of this paper it to open up debate within the environmental modelling and software (EMS) community on how best to respond to the increasing desire to evaluate the success of EMS ...projects in terms of outcomes rather than outputs. Outcomes in these regards are changes beyond the walls of the research organisation (typically to values, attitudes and behaviour). The authors recognise that outcome evaluation is essential in ensuring the relevance and effectiveness of activities. To date, however, there is a limited appreciation within the EMS community of the nature of the challenge inherent in outcome evaluations. The paper presents an exploratory analysis of the challenges that outcome assessment raises for EMS. It does so using mutually reinforcing conceptual and practical perspectives. The paper presents a conceptual framework of three loosely coupled phases – research, development and operations. The nature of activities and their interactions within these phases is outlined and the forms of evaluation associated with each stage set out. The paper notes how existing forms of evaluation (e.g. peer review, validation and relevance) underpin the delivery of outcomes but do not of themselves evaluate outcomes. The paper proposes that outcomes need conceptually to be seen as an element of complex social processes mediated by government, regulation, markets and the media rather than as simply another form of output from research and development projects. As such outcomes of EMS are: less easily tangible than are outputs; more likely to occur at a significant time lag after any intervention; more difficult to assign causality for and to be subject to significant contestation. Thus EMS activity, however well conducted technically, may only have a minor influence on outcomes and EMS practitioners will have limited control over those outcomes that do occur. The paper uses a series of linked EMS projects to populate the conceptual framework showing the role of evaluations in research, development and operations phases. The paper then presents two forms (quantitative and qualitative) of outcome evaluation used as part of an operational phase evaluation of a project communicating the consequences of climate change to remote-rural land managers in Scotland. The authors conclude that while the challenges of EMS evaluation can be met, there needs to be care from the EMS community not to raise expectations of outcomes that cannot be met.
The paper presents the results of a study that developed and applied social metabolism methods to assess the sustainability of a regional economy, particularly the dynamics related to changes in the ...production and use of energy. The first objective of the study was to assess the feasibility of using existing secondary data sources as a basis for sub-nation state and regional analysis (with the regions in this case differentiating the area based on rurality). The second was to structure the outputs of the analysis in ways that provided comprehensive yet succinct and interpretable assessments of the balance of flows of material, energy and money that underpin the economy, with the intention that ultimately these assessments would be used to inform policymaking. The paper provides an introduction to the key concepts used within social metabolism analysis particularly the use of emergy (a measure of the cumulative environmental support provided to a social-ecological system). This is a unifying metric into which the myriad flows within an economy can be translated and combined in meaningful ways. It does so by, preserving information on both the quantity and quality of flows and so avoiding the need for arbitrary weightings. The paper presents a range of options for the use of emergy-based metrics that could be used to inform policy making. Comparisons for the years 2001 and 2010 are made at country level for Scotland and for three degrees of rurality. The analysis highlights how decisions on the share of the offshore energy sector attributed to Scotland and on the share of services (particularly those imported from beyond U.K.) have profound effects on the sustainability trajectory of the economy and the conclusions that might be drawn for policy. The paper concludes that the methods have the potential to add value to existing administrative datasets, and provide new perspectives that may be of value to policy making, but acknowledges that challenges remain in translating this potential into tangible use within policymaking.
•The social metabolism of Scotland is investigated for two time periods 2001 and 2010.•Emergy based metrics are used to inform policy making.•Decisions on the attribution of offshore energy sector have profound effects on the conclusions.•Emergy has the potential to provide new perspectives that may be of value to policy making.•Results confirm concerns that trajectories of change are still toward unsustainability.
► Agro-meteorological metrics were estimated using observed and downscaled RCM data. ► These characterise climate change impacts on land use and ecosystem services. ► Issues of uncertainty arising ...from climate model data use are addressed. ► Weather and soil interactions will be substantially different in the future. ► Implications for strategic planning for land management changes are discussed.
Agro-meteorological metrics are indicators of weather determined environmental conditions on which agricultural management decisions are made. Metrics derived from an estimated future climate provide an opportunity to characterise the impacts of climate change on a wide range of agricultural systems, land use practices and ecosystem services. Such indications are vital for determining how changes in the biophysical environment can lead to land management and policy adaptations to achieve multiple objectives of financial viability, food security, biodiversity conservation and environmental sustainability. They provide valuable links between probable management adaptation responses and capacity for mitigating greenhouse gas emissions. However, there are large uncertainties associated with projected future climates, including the climate models’ spatial scale of representation and those at which agro-meteorological metrics are applied. This paper describes the estimation of agro-meteorological metrics derived from observed weather and downscaled Regional Climate Model projection data for 12 sites in Scotland. Results show that projected changes to seasonal rainfall distribution, growing season length, soil moisture deficits and accessibility will be substantially different from the present climate. Fundamentally, the metrics indicate a substantial shift in land management requirements and potential need for substantial changes in agricultural systems and land use that will have implications across a wide range of research disciplines.
The COVID‐19 pandemic is a major shock to society in terms of health and economy that is affecting both UK and global food and nutrition security. It is adding to the ‘perfect storm’ of threats to ...society from climate change, biodiversity loss and ecosystem degradation, at a time of considerable change, rising nationalism and breakdown in international collaboration. In the UK, the situation is further complicated due to Brexit. The UK COVID‐19 Food and Nutrition Security project, lasting one year, is funded by the Economic and Social Research Council and is assessing the ongoing impact of COVID‐19 on the four pillars of food and nutrition security: access, availability, utilisation and stability. It examines the food system, how it is responding, and potential knock on effects on the UK’s food and nutrition security, both in terms of the cascading risks from the pandemic and other threats. The study provides an opportunity to place the initial lessons being learnt from the on‐going responses to the pandemic in respect of food and nutrition security in the context of other long‐term challenges such as climate change and biodiversity loss.
Wither agricultural DSS? Matthews, K.B.; Schwarz, G.; Buchan, K. ...
Computers and electronics in agriculture,
05/2008, Letnik:
61, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Computer-based agricultural decision support systems (aDSS) may be argued to have passed sequentially through phases of unbelief, euphoria and disappointment, and to be currently passing into either ...a phase of maturity with realistic expectations of the technology, or to abandonment. This paper appraises, in the context of the DSS development literature, our past and current efforts in decision support using simulation-models and farm-scale case-studies. The paper first reviews some of the explanations for the lack of success for aDSS including the identification of suitable roles and how best the tools may be deployed. The paper then outlines the authors’ experiences during the euphoric period of aDSS development including the undertaking of market research on the nature of the aDSS desired and their potential for commercialisation. The positive outcome of the market research was that potential end-users recognised the range of functionality that an aDSS could offer. There was, however, significant scepticism on the balance of costs and benefits. The end-user preference for aDSS delivered as software products for use in-house, when combined with the limits on the price-per-unit that the market would bear, meant that there was little commercial potential. In the light of these findings the team re-evaluated the role and development strategy for their aDSS. The paper outlines this strategy in terms of both the technical developments of the aDSS and the approach to its use with stakeholders. The paper then discusses the legacy from the euphoric period highlighting a number of socio-political and institutional barriers to the use of aDSS which remain to be overcome. The paper concludes by arguing that there is a need to think beyond technocentric solutions to overcome the barriers to wider aDSS use and that there are a number of models of best-practice for aDSS development that can ensure their relevance.
Meteorological station records often consist only of precipitation and air temperature data. There is therefore a need for appropriate methods to estimate solar radiation data to enable complete data ...set creation, by combining observed and estimated data. It is important to know the quality and characteristics of the estimates made in order to understand what impacts the data may have on the use to which they are put. This paper describes a detailed evaluation of the performance and characteristic behaviour of two air temperature based models and one sunshine duration conversion method of estimating solar radiation, for 24 meteorological stations in Britain. Comparisons were made using a fuzzy-logic based multiple-indices assessment system (Irad) and tests of the temporal distribution of mean errors over a year. The conversion from sunshine duration to solar radiation produces the best overall estimates, but shows systematic seasonal errors. The two air temperature based methods can be reliable alternatives when only air temperature data are available. Fundamentally, the study demonstrates the value and importance of using a range of assessment methods to evaluate model estimates.
This paper argues that an integrated assessment (IA) approach, combining simulation modelling with deliberative processes involving decision makers and other stakeholders, has the potential to ...generate credible and relevant assessments of climate change impacts on farming systems. The justification for the approach proposed is that while simulation modelling provides an effective way of exploring the range of possible impacts of climate change and a means of testing the consequences of possible management or policy interventions, the interpretation of the outputs is highly dependent on the point of view of the stakeholder. Inevitably, whatever the responses to climate change, there will be trade-offs between the benefits and costs to a range of stakeholders. The use of a deliberative process that includes stakeholders, both in defining the topics addressed and in debating the interpretations of the outcomes, addresses many of the limitations that have been previously identified in the use of computer-based tools for agricultural decision support. The paper further argues that the concepts of resilience and adaptive capacity are useful for the assessment of climate change impacts as they provide an underpinning theory for processes of change in land use systems. The integrated modelling framework (IMF) developed for the simulation of whole-farm systems is detailed, including components for crop and soil processes, livestock systems and a tool for scheduling of resource use within management plans. The use of the IMF for assessing climate change impacts is then outlined to demonstrate the range of analyses possible. The paper concludes with a critique of the IA approach and notes that issues of quantification and communication of uncertainty are central to the success of the methodology.
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