|   | 
Details
   web
Records
Author Graversgaard, M.; Hedelin, B.; Smith, L.; Gertz, F.; Höjberg, A.L.; Langford, J.; Martinez, G.; Mostert, E.
Title Opportunities and Barriers for Water Co-Governance – A Critical Analysis of Seven Cases of Diffuse Water Pollution from Agriculture in Europe, Australia and North America Type Journal Article
Year 2018 Publication Sustainability Abbreviated Journal Sustainability
Volume 10 Issue 5 Pages 1634
Keywords collaborative governance; decentralized decision-making; non-point source pollution; nutrient management; water governance; management; policy; river; eutrophication; phosphorus; resources; nitrogen; hypoxia; quality; options
Abstract Diffuse Water Pollution from Agriculture (DWPA) and its governance has received increased attention as a policy concern across the globe. Mitigation of DWPA is a complex problem that requires a mix of policy instruments and a multi-agency, broad societal response. In this paper, opportunities and barriers for developing co-governance, defined as collaborative societal involvement in the functions of government, and its suitability for mitigation of DWPA are reviewed using seven case studies in Europe (Poland, Denmark, Sweden, The Netherlands and UK), Australia (Murray-Darling Basin) and North America (State of Minnesota). An analytical framework for assessing opportunities and barriers of co-governance was developed and applied in this review. Results indicated that five key issues constitute both opportunities and barriers, and include: (i) pressure for change; (ii) connected governance structures and allocation of resources and funding; (iii) leadership and establishment of partnerships through capacity building; (iv) use and co-production of knowledge; and (v) time commitment to develop water co-governance.
Address 2018-07-12
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2071-1050 ISBN Medium
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5205
Permanent link to this record
 

 
Author Holman, I.P.; Brown, C.; Carter, T.R.; Harrison, P.A.; Rounsevell, M.
Title Improving the representation of adaptation in climate change impact models Type Journal Article
Year 2019 Publication Regional Environmental Change Abbreviated Journal Reg. Environ. Change
Volume 19 Issue 3 Pages 711-721
Keywords Adaptive capacity; Limits; Water; Land; Decision making; Integrated assessment; Land-Cover Change; Global Change; River-Basin; Integrated Assessment; Adaptive Capacity; Vulnerability; Variability; Precautionary; Agriculture; Management
Abstract Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.
Address 2019-04-27
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1436-3798 ISBN Medium Article
Area Expedition Conference
Notes TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5220
Permanent link to this record
 

 
Author Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Gulzari, S.O.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sandor, R.; Schoenhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V.
Title To what extent is climate change adaptation a novel challenge for agricultural modellers Type Journal Article
Year 2019 Publication Environmental Modelling & Software Abbreviated Journal Env. Model. Softw.
Volume 120 Issue Pages Unsp 104492
Keywords Adaptation; Agricultural modelling; Climate change; Research challenges; greenhouse-gas emissions; farm-level adaptation; land-use; food; security; adapting agriculture; livestock production; decision-making; change impacts; dairy farms; crop
Abstract Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change.
Address 2020-02-14
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1364-8152 ISBN Medium Article
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5223
Permanent link to this record
 

 
Author Mandryk, M.; Reidsma, P.; Kanellopoulos, A.; Groot, J.C.J.; van Ittersum, M.K.
Title The role of farmers’ objectives in current farm practices and adaptation preferences: a case study in Flevoland, the Netherlands Type Journal Article
Year 2014 Publication Regional Environmental Change Abbreviated Journal Reg Environ Change
Volume 14 Issue 4 Pages 1463-1478
Keywords multi-criteria decision-making; multi-objective optimization; agriculture; arable farm; vegetable farms; climate-change; south uruguay; land-use; design; agriculture; model; management; options; systems
Abstract The diversity in farmers’ objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers’ stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers’ objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers’ stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1436-3798 1436-378x ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4794
Permanent link to this record
 

 
Author Mansouri, M.; Destain, M.-F.
Title Predicting biomass and grain protein content using Bayesian methods Type Journal Article
Year 2015 Publication Stochastic Environmental Research and Risk Assessment Abbreviated Journal Stoch. Environ. Res. Risk Assess.
Volume 29 Issue 4 Pages 1167-1177
Keywords crop model; particle filter; prediction; ensemble kalman filter; parameter-estimation; particle filters; decision-support; state estimation; model; nitrogen; navigation; tracking; systems
Abstract This paper deals with the problem of predicting biomass and grain protein content using improved particle filtering (IPF) based on minimizing the Kullback-Leibler divergence. The performances of IPF are compared with those of the conventional particle filtering (PF) in two comparative studies. In the first one, we apply IPF and PF at a simple dynamic crop model with the aim to predict a single state variable, namely the winter wheat biomass, and to estimate several model parameters. In the second study, the proposed IPF and the PF are applied to a complex crop model (AZODYN) to predict a winter-wheat quality criterion, namely the grain protein content. The results of both comparative studies reveal that the IPF method provides a better estimation accuracy than the PF method. The benefit of the IPF method lies in its ability to provide accuracy related advantages over the PF method since, unlike the PF which depends on the choice of the sampling distribution used to estimate the posterior distribution, the IPF yields an optimum choice of this sampling distribution, which also utilizes the observed data. The performance of the proposed method is evaluated in terms of estimation accuracy, root mean square error, mean absolute error and execution times.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1436-3240 1436-3259 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4664
Permanent link to this record