Adaptive decision-making under conditions of uncertainty: the case of farming in the Volta delta, Ghana
Sarku, Rebecca ; Dewulf, Art ; Slobbe, Erik van; Termeer, Katrien ; Kranjac-Berisavljevic, Gordana - \ 2020
Journal of integrative Environmental Sciences 17 (2020)1. - ISSN 1943-815X - p. 1 - 33.
Ada East District - Adaptive decision-making - deltas - farming - uncertainty - weather conditions
Farming in Ghana’s Volta delta is increasingly affected by variability in rainfall conditions and changes in land-use patterns. Under such socio-ecological conditions, little is known about farmers’ decision-making in response to uncertainties in uncertain rainfall conditions. To fill this gap and add to the literature on adaptive decision-making, we addressed the central question: what are the existing patterns of farming decision-making under uncertain rainfall conditions, and which decision-making strategies are adaptive? We developed an adaptive decision-making framework to investigate the behavior of farmers under variable rainfall conditions in Ghana’s Volta delta in the Ada East District. We conducted 5 interviews with agricultural extension agents, 44 in-depth interviews and 4 focus group discussion with farmers. Subsequently, we interviewed a sub-selection of 32 farmers. Findings of the study shows that farmers carry out different decision-making patterns in response to the variable rainfall conditions. We distinguished six strategies: three based on flexibility and three based on robustness. Flexible adaptive decision-making strategies are switching dates for sowing seeds through wait-and-see or delay strategy, muddling through the farming season with the application of various options and alternative irrigation strategies. Robust adaptive decision-making strategies are portfolio strategy of transplanting seedlings in batches, selection of robust (hardy) crops, and intercropping or diversification. Based on how farmers select strategies in response to uncertainty in rainfall conditions, we argue that some decision-making strategies are more adaptive than others. Findings of this study are relevant for the design and implementation of climate related agricultural projects.
Evaluation of Multicriteria Decision Analysis Algorithms in Food Safety: A Case Study on Emerging Zoonoses Prioritization
Garre, Alberto ; Boué, Geraldine ; Fernández, Pablo S. ; Membré, Jeanne Marie ; Egea, Jose A. - \ 2020
Risk Analysis 40 (2020)2. - ISSN 0272-4332 - p. 336 - 351.
Food safety management - MCDA - prioritization - risk ranking - uncertainty
Decision making in food safety is a complex process that involves several criteria of different nature like the expected reduction in the number of illnesses, the potential economic or health-related cost, or even the environmental impact of a given policy or intervention. Several multicriteria decision analysis (MCDA) algorithms are currently used, mostly individually, in food safety to rank different options in a multifactorial environment. However, the selection of the MCDA algorithm is a decision problem on its own because different methods calculate different rankings. The aim of this study was to compare the impact of different uncertainty sources on the rankings of MCDA problems in the context of food safety. For that purpose, a previously published data set on emerging zoonoses in the Netherlands was used to compare different MCDA algorithms: MMOORA, TOPSIS, VIKOR, WASPAS, and ELECTRE III. The rankings were calculated with and without considering uncertainty (using fuzzy sets), to assess the importance of this factor. The rankings obtained differed between algorithms, emphasizing that the selection of the MCDA method had a relevant impact in the rankings. Furthermore, considering uncertainty in the ranking had a high influence on the results. Both factors were more relevant than the weights associated with each criterion in this case study. A hierarchical clustering method was suggested to aggregate results obtained by the different algorithms. This complementary step seems to be a promising way to decrease extreme difference among algorithms and could provide a strong added value in the decision-making process.
Storage Policies: Stockpiling Versus Immediate Release
Wesseler, Justus - \ 2019
Journal of Agricultural and Food Industrial Organization (2019). - ISSN 2194-5896
food crisis - grain reserves - hoarding - stockpiling - storage - uncertainty
Storage policies are used in many countries to smooth price volatility and thereby support food security. When there is a global decrease in food supply caused by a number of extreme weather effects, food reserves are expected to reduce the potential negative implications for households with low purchasing power. In this paper, the properties of such a stockpiling policy are assessed and compared to a policy with storage but without stockpiling. The results show that a stockholding policy is an expensive strategy that generates economic benefits only in extreme cases.
Robotic-cell scheduling with pick-up constraints and uncertain processing times
Tonke, Daniel ; Grunow, Martin ; Akkerman, Renzo - \ 2019
IISE Transactions 51 (2019)11. - ISSN 2472-5854 - p. 1217 - 1235.
automated manufacturing equipment - cyclic scheduling - optimization - Robotic-cell scheduling - uncertainty
Technological developments have propelled the deployment of robots in many applications, which has led to the trend to integrate an increasing number of uncertain processes into robotic and automated equipment. We contribute to this domain by considering the scheduling of a dual-gripper robotic cell. For systems with one potential bottleneck, we determine conditions under which the widely used swap sequence does not guarantee optimality or even feasibility and prove that optimal schedules can be derived under certain conditions when building on two types of slack we introduce. With the addition of a third type of slack and the concept of fixed partial schedules, we develop an offline-online scheduling approach that, in contrast with previous work, is able to deal with uncertainty in all process steps and robot handling tasks, even under pick-up constraints. The approach can deal with single- or multiple-bottleneck systems, and is the first approach that is not restricted to a single predefined sequence such as the swap sequence. Our approach is well suited for real-world applications, since it generates cyclic schedules and allows integration into commonly-used frameworks for robotic-cell scheduling and control. We demonstrate the applicability of our approach to cluster tools in semiconductor manufacturing, showing that our approach generates feasible results for all tested levels of uncertainty and optimal or near-optimal results for low levels of uncertainty. With additional symmetry-breaking constraints, the model can be efficiently applied to industrial-scale test instances. We show that reducing uncertainty to below 10% of the processing time would yield significantly improved cycle lengths and throughput. We also demonstrate that the widely used swap sequence only finds solutions for less than 1% of the instances when strict pick-up constraints are enforced and processing times are heterogeneous. As our approach finds feasible solutions to all of these instances, it enables the application of robotic cells to a significantly broader application environment.
Dealing with uncertainty in collaborative planning: developing adaptive strategies for the IJsselmeer
Zandvoort, Mark ; Brugge, Rutger van der; Vlist, Maarten J. van der; Brink, Adri van den - \ 2019
Journal of Environmental Planning and Management 62 (2019)2. - ISSN 0964-0568 - p. 248 - 265.
adaptive planning - collaborative water management - flexibility - responsibility - uncertainty
Adaptive strategies to deal with uncertainty in water management are often collaboratively developed. So far, however, little attention has been paid to the influence of collaboration on handling uncertainty through adaptive planning. In this paper, we study how collaboration has influenced the handling of uncertainty through adaptive planning for water management strategies for the IJsselmeer area in the Netherlands. We show how a fixation on certainty, different perspectives among actors and unclear responsibilities between arenas affect the handling of uncertainty, and found that it is adversely affected by collaboration. The use of adaptive planning challenged current water uses and system functions, creating resistance from actors. We conclude that developing a shared problem perception, creating a common understanding of uncertainties and ensuring a clear demarcation between the water system, its societal functions and water usage, are necessary to make adaptive planning successful in handling uncertainty.
Automated body weight prediction of dairy cows using 3-dimensional vision
Song, X. ; Bokkers, E.A.M. ; Tol, P.P.J. van der; Groot Koerkamp, P.W.G. ; Mourik, S. van - \ 2018
Journal of Dairy Science 101 (2018)5. - ISSN 0022-0302 - p. 4448 - 4459.
automation - dairy cattle - morphological trait - three-dimensional vision - uncertainty
The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure.
Navigating amid uncertainty in spatial planning
Zandvoort, Mark ; Vlist, Maarten J. Van der; Klijn, Frans ; Brink, Adri Van den - \ 2018
Planning Theory 17 (2018)1. - ISSN 1473-0952 - p. 96 - 116.
ambiguity - climate change - long-term consequences - moral responsibility - spatial planning - uncertainty
In view of the need to adapt to uncertain climate change through spatial interventions, this article explores how spatial planners might navigate amid uncertainty. To draw out insights for planning, we examine planning frameworks which explicitly recognise uncertainty and uncertainty descriptions from studies in environmental risk and climate uncertainty. We build our case by addressing the implications of different characteristics of uncertainty and describe how planners can handle uncertainty based on the nature, level and location of uncertainty. We argue that a plural–unequivocal characterisation of uncertainty helps planners in their search for adequate and warranted interventions amid uncertainty.
Handling uncertainty through adaptiveness in planning approaches : comparing adaptive delta management and the water diplomacy framework
Zandvoort, M. ; Vlist, M.J. van der; Brink, A. van den - \ 2018
Journal of Environmental Policy and Planning 20 (2018)2. - ISSN 1523-908X - p. 183 - 197.
Adaptiveness - environmental planning - planning approaches - uncertainty - water management
Planners and water managers seek to be adaptive to handle uncertainty through the use of planning approaches. In this paper, we study what type of adaptiveness is proposed and how this may be operationalized in planning approaches to adequately handle different uncertainties. We took a comparative case study approach to study two planning approaches: the water diplomacy framework (WDF) and adaptive delta management (ADM). We found that the approaches differ in their conceptualization of uncertainty and show that different types of adaptiveness are used in the approaches. While WDF builds on collaborative adaptive management as a set of ongoing adjustments and continuous learning to handle uncertainty, ADM deliberately attempts to anticipate future adaptations through a set of tools which allows for seizing opportunities and avoiding lock-in and lock-out mechanisms. We conclude that neither of the approaches is fully able to account for different uncertainties. Both approaches may benefit from specific insights in what uncertainty and adaptiveness entail for the development of water management plans.
Planning amid uncertainty : Adaptiveness for spatial interventions in delta areas
Zandvoort, Mark - \ 2017
Wageningen University. Promotor(en): A. van den Brink, co-promotor(en): M.J. Vlist; F. Klijn. - Wageningen : Wageningen University - ISBN 9789463437158 - 242
physical planning - deltas - climatic change - risk management - uncertainty - ruimtelijke ordening - delta's - klimaatverandering - risicobeheersing - onzekerheid
Planning for delta areas happens amid uncertainty, which may influence the location, type and form of interventions such as infrastructure, spatial strategies and design standards. Interventions, however, may fix the spatial configuration for decades, for which insight in the appropriate use of adaptiveness to account for uncertainty is essential. This thesis explores uncertainty and adaptiveness in spatial planning and studies their expression and empirical manifestation in planning approaches, planning tools and planning processes. Uncertainty’s characteristics are used to distill information about the (in)adequacy of specific interventions and are related to three domains of adaptiveness: adaptive management, adaptive capacity and adaptive planning. The thesis shows that while some uncertainties demand interventions aimed at ensuring the effectiveness of planning while anticipating future change, others require a focus on the planning process by the co-construction of knowledge, deliberating about values and increasing the adaptive capacity of actors and institutions.
Statistical modelling of variability and uncertainty in risk assessment of nanoparticles
Jacobs, R. - \ 2016
Wageningen University. Promotor(en): Cajo ter Braak, co-promotor(en): Hilko van der Voet. - Wageningen : Wageningen University - ISBN 9789462578197 - 205
modeling - statistics - particles - risk assessment - uncertainty - uncertainty analysis - nanotechnology - probabilistic models - modelleren - statistiek - deeltjes - risicoschatting - onzekerheid - onzekerheidsanalyse - nanotechnologie - waarschijnlijkheidsmodellen
Engineered nanoparticles (ENPs) are used everywhere and have large technological and economic potential. Like all novel materials, however, ENPs have no history of safe use. Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the societal acceptance and safe use of nanotechnology.
Risk assessment of ENPs has been hampered by lack of knowledge about ENPs, their environmental fate, toxicity, testing considerations, characterisation of nanoparticles and human and environmental exposures and routes. This lack of knowledge results in uncertainty in the risk assessment. Moreover, due to the novelty of nanotechnology, risk assessors are often confronted with small samples of data on which to perform a risk assessment. Dealing with this uncertainty and the small sample sizes are main challenges when it comes to risk assessment of ENPs. The objectives of this thesis are (i) to perform a transparent risk assessment of nanoparticles in the face of large uncertainty in such a way that it can guide future research to reduce the uncertainty and (ii) to evaluate empirical and parametric methods to estimate the risk probability in the case of small sample sizes.
To address the first objective, I adapted an existing Integrated Probabilistic Risk Assessment (IPRA) method for use in nanoparticle risk assessment. In IPRA, statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment in a two-dimensional Monte Carlo algorithm. This method was applied in a human health (nanosilica in food) and an environmental (nanoTiO2 in water) risk context. I showed that IPRA leads to a more transparent risk assessment and can direct further environmental and toxicological research to the areas in which it is most needed.
For the second objective, I addressed the problem of small sample size of the critical effect concentration (CEC) in the estimation of R = P(ExpC > CEC), where ExpC is the exposure concentration. First I assumed normality and investigated various parametric and non-parametric estimators. I found that, compared to the non-parametric estimators, the parametric estimators enable us to better estimate and bound the risk when sample sizes and/or small risks are small. Moreover, the Bayesian estimator outperformed the maximum likelihood estimators in terms of coverage and interval lengths. Second, I relaxed the normality assumption for the tails of the exposure and effect distributions. I developed a mixture model to estimate the risk, R = P(ExpC > CEC), with the assumption of a normal distribution for the bulk data and generalised Pareto distributions for the tails. A sensitivity analysis showed significant influence of the tail heaviness on the risk probability, R, especially for low risks.
In conclusion, to really be able to focus the research into the risks of ENPs to the most needed areas, probabilistic methods as used and developed in this thesis need to be implemented on a larger scale. With these methods, it is possible to identify the greatest sources of uncertainty. Based on such identification, research can be focused on those areas that need it most, thereby making large leaps in reducing the uncertainty that is currently hampering risk assessment of ENPs.
Effect of spatial sampling from European flux towers for estimating carbon and water fluxes with artificial neural networks
Papale, Dario ; Black, T.A. ; Carvalhais, Nuno ; Cescatti, Alessandro ; Chen, Jiquan ; Jung, Martin ; Kiely, Gerard ; Lasslop, Gitta ; Mahecha, Miguel D. ; Margolis, Hank ; Merbold, Lutz ; Montagnani, Leonardo ; Moors, Eddy ; Olesen, J.E. ; Reichstein, Markus ; Tramontana, Gianluca ; Gorsel, Eva Van; Wohlfahrt, Georg ; Ráduly, Botond - \ 2015
Journal of Geophysical Research: Biogeosciences 120 (2015)10. - ISSN 2169-8953 - p. 1941 - 1957.
artificial neural networks - gross primary production - latent heat - representativeness - uncertainty - upscaling
Empirical modeling approaches are frequently used to upscale local eddy covariance observations of carbon, water, and energy fluxes to regional and global scales. The predictive capacity of such models largely depends on the data used for parameterization and identification of input-output relationships, while prediction for conditions outside the training domain is generally uncertain. In this work, artificial neural networks (ANNs) were used for the prediction of gross primary production (GPP) and latent heat flux (LE) on local and European scales with the aim to assess the portion of uncertainties in extrapolation due to sample selection. ANNs were found to be a useful tool for GPP and LE prediction, in particular for extrapolation in time (mean absolute error MAE for GPP between 0.53 and 1.56 gC m-2 d-1). Extrapolation in space in similar climatic and vegetation conditions also gave good results (GPP MAE 0.7-1.41 gC m-2 d-1), while extrapolation in areas with different seasonal cycles and controlling factors (e.g., the tropical regions) showed noticeably higher errors (GPP MAE 0.8-2.09 gC m-2 d-1). The distribution and the number of sites used for ANN training had a remarkable effect on prediction uncertainty in both, regional GPP and LE budgets and their interannual variability. Results obtained show that for ANN upscaling for continents with relatively small networks of sites, the error due to the sampling can be large and needs to be considered and quantified. The analysis of the spatial variability of the uncertainty helped to identify the meteorological drivers driving the uncertainty. Key Points Uncertainty due to spatial sampling is evaluated using ANNs and FLUXNET data GPP and LE budgets and IAV are analyzed with different site networks The uncertainty in upscaling due to spatial sampling is highly heterogeneous
Propagation of positional error in 3D GIS : estimation of the solar irradiation of building roofs
Biljecki, Filip ; Heuvelink, Gerard B.M. ; Ledoux, Hugo ; Stoter, Jantien - \ 2015
International Journal of Geographical Information Science 29 (2015)12. - ISSN 1365-8816 - p. 2269 - 2294.
3D GIS - CityGML - error propagation - photovoltaic potential - uncertainty
While error propagation in GIS is a topic that has received a lot of attention, it has not been researched with 3D GIS data. We extend error propagation to 3D city models using a Monte Carlo simulation on a use case of annual solar irradiation estimation of building rooftops for assessing the efficiency of installing solar panels. Besides investigating the extension of the theory of error propagation in GIS from 2D to 3D, this paper presents the following contributions. We (1) introduce varying XY/Z accuracy levels of the geometry to reflect actual acquisition outcomes; (2) run experiments on multiple accuracy classes (121 in total); (3) implement an uncertainty engine for simulating acquisition positional errors to procedurally modelled (synthetic) buildings; (4) perform the uncertainty propagation analysis on multiple levels of detail (LODs); and (5) implement Solar3Dcity – a CityGML-compliant software for estimating the solar irradiation of roofs, which we use in our experiments. The results show that in the case of the city of Delft in the Netherlands, a 0.3/0.6 m positional uncertainty yields an error of 68 kWh/m2/year (10%) in solar irradiation estimation. Furthermore, the results indicate that the planar and vertical uncertainties have a different influence on the estimations, and that the results are comparable between LODs. In the experiments we use procedural models, implying that analyses are carried out in a controlled environment where results can be validated. Our uncertainty propagation method and the framework are applicable to other 3D GIS operations and/or use cases. We released Solar3Dcity as open-source software to support related research efforts in the future.
Robustness of life cycle assessment results : influence of data variation and modelling choices on results for beverage packaging materials
Harst-Wintraecken, E.J.M. van der - \ 2015
Wageningen University. Promotor(en): Carolien Kroeze, co-promotor(en): Jose Potting. - Wageningen : Wageningen University - ISBN 9789462575097 - 217
levenscyclusanalyse - onzekerheid - modelleren - gegevensanalyse - gegevens verzamelen - afvalverwerking - recycling - milieueffect - life cycle assessment - uncertainty - modeling - data analysis - data collection - waste treatment - recycling - environmental impact
Life cycle assessment (LCA) is a well-established method to evaluate the potential environmental impacts of product and service systems throughout their life cycles. However, it can happen that LCAs for the same product have different and even conflicting outcomes. LCA results need to be robust and trustworthy if they are used in decision making. The aim of this thesis is to evaluate whether the use of multiple data sets and multiple modelling options can increase the robustness of LCA results.
The research starts with identifying reasons for differences in LCA results for the same product. The results of ten existing LCAs for disposable beverage cups are compared to each other as to examine the consistency and robustness of these results. The comparison of the LCAs shows no consistent best or worst cup material. And, the quantitative results for cups made from the same material vary across the LCAs. The evaluation of the methodological choices and the used data sources in each LCA made it possible to identify possible sources for discrepancies in the LCA results. Reasons for differences in results include the variation in the properties of the cups, production processes, waste treatment options, allocation options, choices in system boundaries, impact indicators, and potentially also the data sets that are used.
The thesis next describes a novel method to evaluate and include the influence of data sets and modelling choices on the LCA results. The method is applied in a case study of a disposable polystyrene (PS) beverage cup. The study purposely uses different data sets from various sources for processes with an influential contribution to the LCA results. The study includes two waste treatment options (incineration and recycling). The multiple data sets represent the variability among processes, and the waste treatments represent choices in the modelling of the life cycle of the PS cup.
This variability among the data sets for a similar process is presented as a spread in the results. This spread in the results for the PS cup is caused by differences in the amount and type of the used resources and energy, reported emissions, the origin of the production location, the time period of data collection, or choices in the value of recycled PS. The overlapping spread in the quantitative results for incineration and recycling prevents a decisive conclusion on the preferred waste treatment option for the PS cups.
Next, the method for the use of multiple data sets and modelling choices is applied in a comparative LCA of disposable beverage cups. Three cups are compared: a PS cup, a polylactic acid cup (PLA, a biobased plastic), and a cup made from biopaper (paper with a lining of biobased-plastic). The waste treatment options consist of incineration and recycling for all three cups, and additionally composting and anaerobic digestion for the PLA and biopaper cup.
The use of multiple data sets and modelling choices leads to a considerable spread in the LCA results of the cups. The results do not point to the most environmentally friendly cup material, and neither to a preferred waste treatment option. The results clearly identify composting, however, as the least preferred waste treatment option for the PLA and biopaper cups. The spread in the results makes the comparison of the results for the cups more complex, but the results provides more robust information for decision makers. The combined inclusion of the variability among data sets and the waste treatment options makes the results more trustworthy.
The thesis then dives deeper into the methodological modelling of recycling in LCA and describes and evaluates six widely used recycling modelling methods: three substitution methods, an allocation method, the recycled-content method, and the equal-share method. The main difference among the six methods lies in the assumption on where and how to apply credits for recycled material in the life cycle of the product.
These six methods are applied in two case studies: a disposable PS beverage cup and an aluminium beverage can. The results for the aluminium can clearly depend on the applied recycling modelling method, the recycling rate of the disposed cans, and the amount of recycled material used in the cans. The results for the PS cup additionally depend on the consideration of a drop in the quality of the recycled PS compared to the original PS, and the other waste treatments (landfilling and incineration) for the cups. Including several recycling modelling methods in the LCA incorporates the various underlying modelling philosophies of the methods, and thus makes the results more robust.
This thesis demonstrates the added value of including multiple data sets and multiple modelling choices in LCA. The use of multiple data sets is especially useful if general processes instead of specific processes are used in the representation of the product system. The use of multiple data sets increases the accuracy of the results, and is a supplemental tool next to statistical methods which increase the precision of the results. The simultaneous handling of variability among data sets and modelling choices is hardly performed in LCA. The method presented in this thesis fills this gap and provides a transparent tool to capture these uncertainties. The trade-off between an increase in the robustness of the results and the additional demand for resources (time, money, effort) should be assessed, and depends on the goal of the study and on the intended use of the results. This thesis shows that inclusion of the uncertainty in the LCA results provides the decision maker with valuable information. This thesis thus provides a useful method to increase the robustness of LCA results.
Loss of animal seed dispersal increases extinction risk in a tropical tree species due to pervasive negative density dependence across life stages
Caughlin, T.T. ; Ferguson, J.M. ; Lichstein, J.W. ; Zuidema, P.A. ; Bunyavejchewin, S. ; Levey, D.J. - \ 2015
Proceedings of the Royal Society. B: Biological Sciences 282 (2015)1798. - ISSN 0962-8452 - 9 p.
spatial-patterns - rain-forest - recruitment - consequences - neighborhood - defaunation - habitat - uncertainty - diversity - abundance
Overhunting in tropical forests reduces populations of vertebrate seed dispersers. If reduced seed dispersal has a negative impact on tree population viability, overhunting could lead to altered forest structure and dynamics, including decreased biodiversity. However, empirical data showing decreased animal-dispersed tree abundance in overhunted forests contradict demographic models which predict minimal sensitivity of tree population growth rate to early life stages. One resolution to this discrepancy is that seed dispersal determines spatial aggregation, which could have demographic consequences for all life stages. We tested the impact of dispersal loss on population viability of a tropical tree species, Miliusa horsfieldii, currently dispersed by an intact community of large mammals in a Thai forest. We evaluated the effect of spatial aggregation for all tree life stages, from seeds to adult trees, and constructed simulation models to compare population viability with and without animal-mediated seed dispersal. In simulated populations, disperser loss increased spatial aggregation by fourfold, leading to increased negative density dependence across the life cycle and a 10-fold increase in the probability of extinction. Given that the majority of tree species in tropical forests are animal-dispersed, overhunting will potentially result in forests that are fundamentally different from those existing now.
Exploring climate change impacts and adaptation options for maize production in the Central Rift Valley of Ethiopia using different climate change scenarios and crop models
Kassie, B.T. ; Asseng, S. ; Rotter, R.P. ; Hengsdijk, H. ; Ruane, A.C. ; Ittersum, M.K. van - \ 2015
Climatic Change 129 (2015)1-2. - ISSN 0165-0009 - p. 145 - 158.
africa - yield - agriculture - risks - opportunities - vulnerability - temperatures - uncertainty - variability - projections
Exploring adaptation strategies for different climate change scenarios to support agricultural production and food security is a major concern to vulnerable regions, including Ethiopia. This study assesses the potential impacts of climate change on maize yield and explores specific adaptation options under climate change scenarios for the Central Rift Valley of Ethiopia by mid-century. Impacts and adaptation options were evaluated using three General Circulation Models (GCMs) in combination with two Representative Concentration Pathways (RCPs) and two crop models. Results indicate that maize yield decreases on average by 20 % in 2050s relative to the baseline (1980–2009) due to climate change. A negative impact on yield is very likely, while the extent of impact is more uncertain. The share in uncertainties of impact projections was higher for the three GCMs than it was for the two RCPs and two crop models used in this study. Increasing nitrogen fertilization and use of irrigation were assessed as potentially effective adaptation options, which would offset negative impacts. However, the response of yields to increased fertilizer and irrigation will be less for climate change scenarios than under the baseline. Changes in planting dates also reduced negative impacts, while changing the maturity type of maize cultivars was not effective in most scenarios. The multi-model based analysis allowed estimating climate change impact and adaptation uncertainties, which can provide valuable insights and guidance for adaptation planning.
Effects of technical interventions on flexibility of farming systems in Burkina Faso: Lessons for the design of innovations in West Africa
Andrieu, N. ; Descheemaeker, K.K.E. ; Sanou, T. ; Chia, E. - \ 2015
Agricultural Systems 136 (2015). - ISSN 0308-521X - p. 125 - 137.
crop-livestock systems - sub-saharan africa - climate-change - smallholder farmers - coping strategies - modeling approach - decision-making - constraints - uncertainty - variability
African farmers have always been exposed to climatic and economic variability and have developed a range of coping strategies. Such strategies form part of flexible farm management, an ability that may prove very valuable in the face of future climate change and market dynamics. The generally low productivity of African smallholder farming systems is usually addressed by research and development institutions by a variety of solutions for improving farm performance. However, changes to the system may affect the flexibility of farms and thus their ability to cope with variability. We quantified the added value of being flexible and how this flexibility is affected by technical changes, such as composting and cattle fattening recurrently proposed and promoted by research and development institutions and projects. The study was conducted in two villages of the agro-pastoral area of Burkina Faso, where livestock, cereals and cotton are the main farming activities. A whole-farm simulation model was developed based on information gathered during focus group meetings with farmers and detailed individual monitoring of farmers' practices. The model simulates farmers' decision rules governing the management of the cropping and livestock farm components, as well as crop and livestock production and farm gross margin. Using the existing decision rules, current farm performance was simulated by assessing the cereal balance, the fodder balance and the whole farm gross margin. Then, by comparing the mean and the coefficient of variation of these indicators resulting from (a) the existing decision rules (baseline scenario) and (b) a set of less flexible rules (rigid scenario), the added value of flexible management was revealed. The adoption of composting practices allowed a slight increase in gross margin associated with a decrease in its between-year variability in comparison with conventional practices. Cattle fattening only led to a higher gross margin in the years with high rainfall and low input prices when no management practices were used to limit dependence on external input. This kind of technical change thus requires increased management agility by farmers to deal with climatic and economic variability. We conclude that assessing the impact of technical interventions not only in terms of productivity but also in terms of changes in flexibility is useful for a better understanding of potential adoption of technical changes
Modelling of adaptation to climate change and decision-makers behaviours for the Veluwe forest area in the Netherlands
Yousefpour, R. ; Didion, M.P. ; Jacobsen, J.B. ; Meilby, H. ; Hengeveld, G.M. ; Schelhaas, M. ; Thorsen, B.J. - \ 2015
Forest Policy and Economics 54 (2015). - ISSN 1389-9341 - p. 1 - 10.
management - uncertainty - future - dynamics - germany - belief - face
We apply Bayesian updating theory to model how decision-makers may gradually learn about climate change and make use of this information in making adaptive forest management decisions. We develop modelling steps to i) simulate observation of a multi-dimensional climate system, ii) apply updating rules for beliefs about climate trends, iii) evaluate the performance of adaptive strategies, and iv) apply (i)–(iii) at the local and forest landscape scale to find and compare individual versus joint adaptive decisions. We search for optimal forest management decisions maximizing total biomass production as a measure of management performance. The results illustrate the benefits of updating beliefs to eventually utilize the positive effects and limit negative impacts of climate change on forest biomass production. We find that adaptive decision-making results in switching decisions over time and mostly differ from deterministic decisions ignoring any change in climate. Moreover, we find that the adaptation strategies are indispensable not only because of climate change but also because of the development of the forest biological system over time and the need to revisit decisions.
The interaction triangle as a tool for understanding stakeholder interactions in marine ecosystem based management
Rockmann, C. ; Leeuwen, J. van; Goldsborough, D.G. ; Kraan, M.L. ; Piet, G.J. - \ 2015
Marine Policy 52 (2015). - ISSN 0308-597X - p. 155 - 162.
traditional ecological knowledge - fisheries management - environmental assessment - citizen participation - resource-management - risk communication - uncertainty - governance - framework - science
Expectations about ecosystem based management (EBM) differ due to diverging perspectives about what EBM should be and how it should work. While EBM by its nature requires trade-offs to be made between ecological, economic and social sustainability criteria, the diversity of cross-sectoral perspectives, values, stakes, and the specificity of each individual situation determine the outcome of these trade-offs. The authors strive to raise awareness of the importance of interaction between three stakeholder groups (decision makers, scientists, and other actors) and argue that choosing appropriate degrees of interaction between them in a transparent way can make EBM more effective in terms of the three effectiveness criteria salience, legitimacy, and credibility. This article therefore presents an interaction triangle in which three crucial dimensions of stakeholder interactions are discussed: (A) between decision makers and scientists, who engage in framing to foster salience of scientific input to decision making, (B) between decision makers and other actors, to shape participation processes to foster legitimacy of EBM processes, and (C) between scientists and other actors, who collaborate to foster credibility of knowledge production. Due to the complexity of EBM, there is not one optimal interaction approach; rather, finding the optimal degrees of interaction for each dimension depends on the context in which EBM is implemented, i.e. the EBM objectives, the EBM initiator’s willingness for transparency and interaction, and other context-specific factors, such as resources, trust, and state of knowledge.
Preparing suitable climate scenario data to assess impacts on local food safety
Liu, C. ; Hofstra, N. ; Leemans, R. - \ 2015
Food Research International 68 (2015). - ISSN 0963-9969 - p. 31 - 40.
stochastic weather generator - multimodel ensemble - change projections - model - precipitation - cmip5 - uncertainty - temperature - calibration - growth
Quantification of climate change impacts on food safety requires food safety assessment with different past and future climate scenario data to compare current and future conditions. This study presents a tool to prepare climate and climate change data for local food safety scenario analysis and illustrates how this tool can be used with impact models, such as bacterial and mycotoxin growth and pesticide models. As an example, coarse gridded data from two global climate models (GCMs), HadGEM2-ES and CCSM4, are selected and downscaled using the “Delta method” with quantile-quantile correction for Ukkel, Belgium. Observational daily temperature and precipitation data from 1981 to 2000 are used as a reference for this downscaling. Data are provided for four future representative concentration pathways (RCPs) for the periods 2031–2050 and 2081–2100. These RCPs are radiative forcing scenarios for which future climate conditions are projected. The climate projections for these RCPs show that both temperature and precipitation will increase towards the end of the century in Ukkel. The climate change data are then used with Ratkowsky's bacterial growth model to illustrate how projected climate data can be used for projecting bacterial growth in the future. In this example, the growth rate of Lactobacillus plantarum in Ukkel is projected to increase in the future and the number of days that the bacteria are able to grow is also projected to increase. This example shows that this downscaling method can be applied to assess future food safety. However, we only used two GCMs. To obtain a more realistic uncertainty range, using many different GCM output datasets and working directly with climate modellers is recommended. Our approach helps food safety researchers to perform their own climate change scenario analysis. The actual algorithm of the downscaling method and its detailed manual is available in the supplementary material.
Rescue and renewal of legacy soil resource inventories: A case study of the Limpopo National Park, Mozambique.
Cambule, A. ; Rossiter, D.G. ; Stoorvogel, J.J. ; Smaling, E.M.A. - \ 2015
Catena 125 (2015). - ISSN 0341-8162 - p. 169 - 182.
acid sulfate soils - carbon sequestration - resurrection - uncertainty - gambia - maps
Many areas of developing countries are covered by legacy soil surveys, which, however are hardly used, as they are not available in digital form, used outdated standards, and have unknown quality. There have been very few attempts to rescue and renew these surveys, nor are there established criteria for the evaluation of their quality. We therefore decided to test the applicability of the Cornell Adequacy Criteria (CAC) to assess the quality of several renewed soil surveys in or near the Limpopo National Park, Mozambique (centroid: 23° 18' 55.57¿ S, 31° 55' 16.24¿ E), using the concepts of digital soilmapping. The qualitywas assessed formapping andmonitoring soil organic carbon (SOC), in terms of geodetic control, positional accuracy, map scale, and texture and adequacy of map legend. Metadata was attached to the renewed maps. SOC stocks were estimated qualitatively based on the description of themap units and quantitatively by themeasure-and-multiply approach fromlegacy laboratory measurements. The positional accuracy of georegistrationwas 13 to 45% of the square root of aMinimumLegible Area (MLA). Point and area-class layers could be created with high positional accuracy. However the index of maximumreductionwas high, indicating that the original publication scale could be reduced.Map unit definitions and overall information content of the surveyswere adequate. Integration of remotely sensed optical imagery and digital elevation models could be used to derive accurate contours, against which the positional accuracy of contour-basedmap borderswas assessed. Less than 30% of their lengths were within a distance equal to the square root of MLA. These sources could not be used to evaluate internal map borders, due to the subdued topography and major land-use changes since the original survey. Qualitative estimates of SOC are between lowand medium, consistent with other studies in this area. The CAC proved to be a useful framework for determining the fitness for use of legacy surveys.
Using ex ante output elicitation to model state-contingent technologies
Chambers, R.G. ; Serra, T. ; Stefanou, S.E. - \ 2015
Journal of Productivity Analysis 43 (2015)1. - ISSN 0895-562X - p. 75 - 83.
technical efficiency - cheap talk - cost - distributions - uncertainty - economics
Survey-elicited ex ante outputs are used to develop an empirical representation of an Arrow–Debreu–Savage state-contingent technology in an activity-analysis framework. An empirical test of output-cubicality is developed for that framework. We apply those tools to assess production characteristics of a sample of Catalan farmers specialized in arable crops. Results suggest that imposing nonsubstitutability between ex ante outputs results in no significant loss of information. Even though the technology appears to be output cubical, efficiency measurements based on ex post output observations do not appear to adequately represent the stochastic production environment and apparently yield downward biased technical efficiency measures.
Simulation testing the robustness of stock assessement models to error: some results from the ICES strategic initiative on stock assessment methods
Deroba, J.J. ; Butterworth, D.S. ; Methot, R.D. ; Dickey-Collas, M. ; Miller, D.C.M. ; Hintzen, N.T. - \ 2015
ICES Journal of Marine Science 72 (2015)1. - ISSN 1054-3139 - p. 19 - 30.
at-age analysis - management procedures - natural mortality - performance - uncertainty - fishery
The World Conference on Stock Assessment Methods (July 2013) included a workshop on testing assessment methods through simulations. The exercise was made up of two steps applied to datasets from 14 representative fish stocks from around the world. Step 1 involved applying stock assessments to datasets with varying degrees of effort dedicated to optimizing fit. Step 2 was applied to a subset of the stocks and involved characteristics of given model fits being used to generate pseudo-data with error. These pseudo-data were then provided to assessment modellers and fits to the pseudo-data provided consistency checks within (self-tests) and among (cross-tests) assessment models. Although trends in biomass were often similar across models, the scaling of absolute biomass was not consistent across models. Similar types of models tended to perform similarly (e.g. age based or production models). Self-testing and cross-testing of models are a useful diagnostic approach, and suggested that estimates in the most recent years of time-series were the least robust. Results from the simulation exercise provide a basis for guidance on future large-scale simulation experiments and demonstrate the need for strategic investments in the evaluation and development of stock assessment methods.
Understanding wicked problems and organized irresponsibility: challenges for governing the sustainable intensification of chicken meat production
Bueren, E.M. ; Lammerts Van Bueren, E. ; Zijpp, A.J. van der - \ 2014
Current Opinion in Environmental Sustainability 8 (2014). - ISSN 1877-3435 - p. 1 - 14.
supply chain management - antibiotic-resistance - escherichia-coli - risk - agriculture - uncertainty - future - issues - green
Framing sustainable intensification as a wicked problem reveals how inherent trade-offs and resulting uncertainty and ambiguity block integrated problem solving as promoted by sustainable chain management approaches to production and consumption. The fragmented institutional set-up of the chains avoids that individual actors take responsibility for risks they helped to produce, resulting in ‘organized irresponsibility’. Governance arrangements for sustainable chain management focus especially on reducing risk and uncertainty and ignore trade-offs instead of acknowledging them. For the Dutch chicken meat chain, this article explores how wicked problems and organized irresponsibility influence governance opportunities for sustainable intensification.
Catchments as simple dynamical systems: A case study on methods and data requirements for parameter indentification.
Melsen, L.A. ; Teuling, A.J. ; Berkum, S.W. van; Torfs, P.J.J.F. ; Uijlenhoet, R. - \ 2014
Water Resources Research 50 (2014)7. - ISSN 0043-1397 - p. 5577 - 5596.
rainfall-runoff models - hydrological model - calibration data - ungauged basins - uncertainty
In many rainfall-runoff models, at least some calibration of model parameters has to take place. Especially for ungauged or poorly gauged basins this can be problematic, because there is little or no data available for calibration. A possible solution to overcome the problems caused by data scarcity is to set up a measurement campaign for a limited time period. In this study, we determine the minimum amount of data required to determine robust parameter values for a simple model with two parameters. The model is constructed such that the parameters can be determined not only with automatic calibration, but also by recession analysis and a priori from Boussinesq theory. The model has been applied to a research catchment in Switzerland. For automatic calibration and recession analysis, one season (5 months) is found to be sufficient to give robust parameters for simulation of high flows over the full observation period. For automatic calibration, this should be the season with the highest precipitation, for recession analysis the season with least evapotranspiration. The Boussinesq equation is able to give good parameter estimates for modeling high flows, but detailed in situ knowledge of the catchment is required. Automatic calibration outperforms recession analysis and Boussinesq theory by far when it comes to parameter estimation with a focus on prediction of low flows. It was shown that a single set of parameters cannot simultaneously describe high and low flows with a reasonable accuracy, suggesting that more than two parameters are needed to characterize subsurface properties.
Editorial : Ensemble prediction and data assimilation for operational hydrology : Editorial
Seo, D.J. ; Liu, Y. ; Moradkhani, H. ; Weerts, A.H. - \ 2014
Journal of Hydrology 519 (2014)part D. - ISSN 0022-1694 - p. 2661 - 2662.
Effects of climate and nutrient load on the water quality of shallow lakes assessed through ensemble runs by PCLake
Nielsen, A. ; Trolle, D. ; Bjerring, R. - \ 2014
Ecological Applications 24 (2014)8. - ISSN 1051-0761 - p. 1926 - 1944.
ecosystem model pclake - danish lakes - phosphorus - state - eutrophication - restoration - equifinality - uncertainty - sensitivity - management
Complex ecological models are used to predict the consequences of anticipated future changes in climate and nutrient loading for lake water quality. These models may, however, suffer from nonuniqueness in that various sets of model parameter values may yield equally satisfactory representations of the system being modeled, but when applied in future scenarios these sets of values may divert considerably in their simulated outcomes. Compilation of an ensemble of model runs allows us to account for simulation variability arising from model parameter estimates. Thus, we propose a new approach for aquatic ecological models creating a more robust prediction of future water quality. We used our ensemble approach in an application of the widely used PCLake model for Danish shallow Lake Arreskov, which during the past two decades has demonstrated frequent shifts between turbid and clear water states. Despite marked variability, the span of our ensemble runs encapsulated 70–90% of the observed variation in lake water quality. The model exercise demonstrates that future warming and increased nutrient loading lead to lower probability of a clear water, vegetation-rich state and greater likelihood of cyanobacteria dominance. In a 6.0°C warming scenario, for instance, the current nutrient loading of nitrogen and phosphorus must be reduced by about 75% to maintain the present ecological state of Lake Arreskov, but even in a near-future 2.0°C warming scenario, a higher probability of a turbid, cyanobacteria-dominated state is predicted. As managers may wish to determine the probability of achieving a certain ecological state, our proposed ensemble approach facilitates new ways of communicating future stressor impacts.
On noice in data assimilation schemes for improved flood forecasting using distributed hydrological models
Noh, S.J. ; Rakovec, O. ; Weerts, A.H. ; Tachikawa, Y. - \ 2014
Journal of Hydrology 519 (2014)part D. - ISSN 0022-1694 - p. 2707 - 2721.
sequential data assimilation - ensemble kalman filter - surface soil-moisture - probabilistic forecasts - river-basin - streamflow - water - uncertainty - states - implementation
We investigate the effects of noise specification on the quality of hydrological forecasts via an advanced data assimilation (DA) procedure using a distributed hydrological model driven by numerical weather predictions. The sequential DA procedure is based on (1) a multivariate rainfall ensemble generator, which provides spatial and temporal correlation error structures of input forcing, and (2) lagged particle filtering to update past and current state variables simultaneously in a lag-time window to consider the response times of internal hydrologic processes. The procedure is evaluated for streamflow forecasting of three flood events in two fast-responding catchments in Japan (Maruyama and Katsura). The rainfall ensembles are derived from ground-based rain gauge observations for the analysis step and numerical weather predictions for the forecast step. The ensemble simulation performs multi-site updating using information from the streamflow gauging network and considers the artificial effects of reservoir release. Sensitivity analysis is performed to assess the impacts of noise specification in DA, comparing a different setup of random state noise and input forcing with/without multivariate conditional simulation (MCS) of rainfall ensembles. The results show that lagged particle filtering (LPF) forced with MCS provides good performance with small and consistent random state noise, whereas LPF forced with Thiessen rainfall interpolation requires larger random state noise to yield performance comparable to that of LPF + MCS for short lead times.
Challenges to scenario-guided adaptive action on food security under climate change
Vervoort, J.M. ; Thornton, P.K. ; Kristjansson, P. ; Foerch, W. ; Ericksen, P.J. ; Kok, K. ; Ingram, J.S. ; Herrero, M. ; Palazzo, A. ; Helfgott, A.E.S. ; Wilkinson, A. ; Havlik, P. ; Mason-D’Croz, D. ; Jost, C. - \ 2014
Global environmental change : human and policy dimensions 28 (2014). - ISSN 0959-3780 - p. 383 - 394.
sustainable development - uncertainty - agriculture - systems - adaptation - knowledge - science - scales
This paper examines the development and use of scenarios as an approach to guide action in multi-level, multi-actor adaptation contexts such as food security under climate change. Three challenges arehighlighted: (1) ensuring the appropriate scope for action; (2) moving beyond intervention-based decision guidance; and (3) developing long-term shared capacity for strategic planning. To overcome these challenges we have applied explorative scenarios and normative back-casting with stakeholders from different sectors at the regional level in East Africa. We then applied lessons about appropriate scope, enabling adaptation pathways, and developing strategic planning capacity to scenarios processes in multiple global regions. Scenarios were created to have a broad enough scope to be relevant to diverse actors, and then adapted by different actor groups to ensure their salience in specific decision contexts. The initial strategy for using the scenarios by bringing a range of actors together to explore new collaborative proposals had limitations as well as strengths versus the application of scenarios for specific actor groups and existing decision pathways. Scenarios development and use transitioned from an intervention-based process to an embedded process characterized by continuous engagement. Feasibility and long-term sustainability could be ensured by having decision makers own the process and focusing on developing strategic planning capacity within their home organizations.
Managing climate change in conservation practice: an exploration of the science–management interface in beech forest management.
Koning, J. de; Turnhout, E. ; Winkel, G. ; Blondet, M. ; Borras, L. ; Ferranti, F. ; Geitzenauer, M. ; Sotirov, M. ; Jump, A. - \ 2014
Biodiversity and Conservation 23 (2014)14. - ISSN 0960-3115 - p. 3657 - 3671.
fagus-sylvatica l. - ecological restoration - policy - future - range - biodiversity - shifts - uncertainty - responses - politics
Scientific studies reveal significant consequences of climate change for nature, from ecosystems to individual species. Such studies are important factors in policy decisions on forest conservation and management in Europe. However, while research has shown that climate change research start to impact on European conservation policies like Natura 2000, climate change information has yet to translate into management practices. This article contributes to the on-going debates about science–society relations and knowledge utilization by exploring and analysing the interface between scientific knowledge and forest management practice. We focus specifically on climate change debates in conservation policy and on how managers of forest areas in Europe perceive and use climate change ecology. Our findings show that forest managers do not necessarily deny the potential importance of climate change for their management practices, at least in the future, but have reservations about the current usefulness of available knowledge for their own areas and circumstances. This suggests that the science–management interface is not as politicized as current policy debates about climate change and that the use of climate change ecology is situated in practice. We conclude the article by discussing what forms of knowledge may enable responsible and future oriented management in practice focusing specifically on the role of reflexive experimentation and monitoring.
Measuring the impacts of production risk on technical efficiency: A state-contingent conditional order-m approach
Serra, T. ; Oude Lansink, A.G.J.M. - \ 2014
European Journal of Operational Research 239 (2014)1. - ISSN 0377-2217 - p. 237 - 242.
nonparametric frontier models - cheap talk - technologies - uncertainty - inference - corn
This article studies the influence of risk on farms' technical efficiency levels. The analysis extends the order-m efficiency scores approach proposed by Daraio and Simar (2005) to the state-contingent framework. The empirical application focuses on cross section data of Catalan specialized crop farms from the year 2011. Results suggest that accounting for production risks increases the technical performance. A 10% increase in output risk will result in a 2.5% increase in average firm technical performance. © 2014 Elsevier B.V. All rights reserved.
Innovation capabilities in food and beverages and technology-based innovation projects
Tepic, M. ; Fortuin, F.T.J.M. ; Kemp, R.G.M. ; Omta, S.W.F. - \ 2014
British Food Journal 116 (2014)2. - ISSN 0007-070X - p. 228 - 250.
product development - success factors - dynamic environments - chinese firms - performance - industry - uncertainty - system - perspectives - acceptance
Purpose - The aim of this paper is to establish the differences between the food and beverages (F&B) and technology-based industries with regards to the relation between previously identified success factors and innovation project performance. Design/methodology/approach - These differences are established on the basis of logistic regression analysis, using 38 innovation projects (18 F&B and 20 technology-based). Findings - Newness of the innovation project to the company, communication capabilities and market potential have a more negative impact on innovation project performance in the F&B than the tech-based industry. Especially functional upstream capabilities increase the likelihood of success in F&B, when compared to tech-based innovation projects. Practical implications - While functional upstream capabilities are important for success of F&B innovation projects, there is still room for improvement in order to deal effectively with newness of the innovation project to the company. Internalization of resources from the network and a balanced radical/incremental innovation project portfolio contribute to additional enhancement of functional capabilities of the F&B companies, improving their capacity to deal with newness. Through a larger focus on co-innovation with retail, F&B companies can improve their intra- and inter-firm communication capabilities to attain more consumer-oriented integration of R&D and marketing activities, improving the market potential of their innovations. Originality/value - This paper demonstrates that the previously identified critical success factors for innovation projects differ in impact and importance for F&B innovation project performance when compared to innovation projects in the technology-based industry.
The economic power of the Golden Rice opposition
Wesseler, J.H.H. ; Zilberman, D. - \ 2014
Environment and Development Economics 19 (2014)6. - ISSN 1355-770X - p. 724 - 742.
birth-weight - vitamin-a - health - uncertainty - benefits - growth - impact - costs - gm
Vitamin A enriched rice (Golden Rice) is a cost-efficient solution that can substantially reduce health costs. Despite Golden Rice being available since early 2000, this rice has not been introduced in any country. Governments must perceive additional costs that overcompensate the benefits of the technology to explain the delay in approval. We develop a real option model including irreversibility and uncertainty about perceived costs and arrival of new information to explain a delay in approval. The model has been applied to the case of India. Results show the annual perceived costs have to be at least US$199 million per year approximately for the last decade to explain the delay in approval of the technology. This is an indicator of the economic power of the opposition towards Golden Rice resulting in about 1.4 million life years lost over the past decade in India.
Stagnating Jatropha Biofuel Development in Southwest China: An Institutional Approach
Li, Jia ; Bluemling, B. ; Mol, A.P.J. ; Herzfeld, Th. - \ 2014
Sustainability 6 (2014)6. - ISSN 2071-1050 - p. 3192 - 3212.
future orientation - forestry - sustainability - perspectives - plantations - uncertainty - investment - management - prospects - biodiesel
Biodiesel from jatropha has been considered as a promising alternative to fossil fuels for some time. Consequently, China started promoting jatropha as one of the options to meet its ever-increasing energy consumption, and the Chinese biodiesel industry also gained interest. However, the excitement of the biofuel industry in jatropha faded after it did not bring about the expected results. This article investigates the stagnation in jatropha development and production for biodiesel in China, using two detailed case studies of jatropha biofuel production in southeast China. It is found that the underdeveloped biodiesel policy and regulation, such as a rather late formulation of standards for biodiesel (especially the B5) and the absence of mandatory targets, is an important reason for hampering jatropha development. Besides that, lack of financial support undermined sustained jatropha planting at the farm level and lack of sustained commitment from state-owned enterprises or private companies over a long time span further contributed to jatropha project’s failure. Better implementation of the rule of law, mandatory blending requirements, hazard insurance, as well as continuous financial support, might improve the continuation of jatropha plantation schemes.
Smallholder participation in large forestry programs: The camellia program in China
Li, J. ; Bluemling, B. ; Dries, L.K.E. ; Feng, S. - \ 2014
Outlook on Agriculture 43 (2014)1. - ISSN 0030-7270 - p. 45 - 51.
influencing peoples participation - land-tenure arrangements - climate-change - investment incentives - burkina-faso - costa-rica - uncertainty - adoption - risk - management
In recent years, many forestry projects have been implemented in developing countries. In China, a variety of large-scale afforestation and reforestation programmes have been carried out with multiple objectives, such as livelihood improvement and carbon sequestration. As in many developing countries, these projects have been implemented in a smallholder context. This paper investigates the determinants of smallholder participation in large forestry projects. Using the case of camellia, it explores the determinants of smallholder participation using a probit regression model. To distinguish between participation in international and government-run projects, a bivariate probit regression model is used. The findings show that only 37% of households in the sample had participated in the Camellia project; a major reason for the low participation rate is perceived tenure insecurity. The results of the bivariate probit model show that the education level of the household head and household size have a positive impact on the likelihood of household participation. The more 'off-farm' activities are taken up in a household, the less likely a household is to participate in an international project. For a government project, household size also has a positive impact on the likelihood of participation. Chinese forestry is diversifying since the devolution of forestland use rights, with a majority of households hesitating to invest, while some risk investment and others depend on government subsidies. The main policy implication is that, if the Chinese government wishes to achieve its goal of 1.68 million hectares of camellia, then improving tenure security is crucial.
Costs and benefits of adapting spatial planning to climate change: lessons learned from a large-scale urban development project in the Netherlands
Bruin, K. de; Goosen, H. ; Ierland, E.C. van; Groeneveld, R.A. - \ 2014
Regional Environmental Change 14 (2014)3. - ISSN 1436-3798 - p. 1009 - 1020.
policy - adaptation - economics - uncertainty - options - risks
Climate change increases the vulnerability of low-lying coastal areas. Careful spatial planning can reduce this vulnerability, provided that decision-makers have insight into the costs and benefits of adaptation options. This paper addresses the question which adaptation options are suitable, from an economic perspective, to adapt spatial planning to climate change at a regional scale. We apply social cost–benefit analysis to assess the net benefits of adaptation options that deal with the impacts of climate change-induced extreme events. From the methods applied and results obtained, we also aim at learning lessons for assessing climate adaptation options. The case study area, the Zuidplaspolder, is a large-scale urban development project in the Netherlands. The costs as well as the primary and secondary benefits of adaptation options relating to spatial planning (e.g. flood-proof housing and adjusted infrastructure) are identified and where possible quantified. Our results show that three adaptation options are not efficient investments, as the investment costs exceed the benefits of avoided damages. When we focus on ‘climate proofing’ the total area of the Zuidplaspolder, when the costs and benefits of all the presented adaptation options are considered together, the total package has a positive net present value. The study shows that it is possible to anticipate climate change impacts and assess the costs and benefits of adjusting spatial planning. We have learned that scenario studies provide a useful tool but that decision-making under climate change uncertainty also requires insight into the probabilities of occurrence of weather extremes in the future.
Merging validation and evaluation of ecological models to evaluation': a review of terminology and a practical approach
Augusiak, J.A. ; Brink, P.J. van den; Grimm, V. - \ 2014
Ecological Modelling 280 (2014). - ISSN 0304-3800 - p. 117 - 128.
individual-based models - risk-assessment - environmental-models - quality-assurance - simulation-model - complex-systems - beech forests - assessments - verification - uncertainty
Confusion about model validation is one of the main challenges in using ecological models for decision support, such as the regulation of pesticides. Decision makers need to know whether a model is a sufficiently good representation of its real counterpart and what criteria can be used to answer this question. Unclear terminology is one of the main obstacles to a good understanding of what model validation is, how it works, and what it can deliver. Therefore, we performed a literature review and derived a standard set of terms. ‘Validation’ was identified as a catch-all term, which is thus useless for any practical purpose. We introduce the term ‘evaludation’, a fusion of ‘evaluation’ and ‘validation’, to describe the entire process of assessing a model's quality and reliability. Considering the iterative nature of model development, the modelling cycle, we identified six essential elements of evaludation: (i) ‘data evaluation’ for scrutinising the quality of numerical and qualitative data used for model development and testing; (ii) ‘conceptual model evaluation’ for examining the simplifying assumptions underlying a model's design; (iii) ‘implementation verification’ for testing the model's implementation in equations and as a computer programme; (iv) ‘model output verification’ for comparing model output to data and patterns that guided model design and were possibly used for calibration; (v) ‘model analysis’ for exploring the model's sensitivity to changes in parameters and process formulations to make sure that the mechanistic basis of main behaviours of the model has been well understood; and (vi) ‘model output corroboration’ for comparing model output to new data and patterns that were not used for model development and parameterisation. Currently, most decision makers require ‘validating’ a model by testing its predictions with new experiments or data. Despite being desirable, this is neither sufficient nor necessary for a model to be useful for decision support. We believe that the proposed set of terms and its relation to the modelling cycle can help to make quality assessments and reality checks of ecological models more comprehensive and transparent. Keywords Model validation; Terminology; Decision support; Documentation; Ecological models; Risk assessment
Why the complex nature of integrated ecosystem assessments requires a flexible and adaptive approach
Dickey-Collas, M. - \ 2014
ICES Journal of Marine Science 71 (2014)5. - ISSN 1054-3139 - p. 1174 - 1182.
fisheries management - ecological indicators - mixed-fisheries - framework - implementation - policy - uncertainty - thresholds - scientists - support
This article considers the approach taken by the ICES to integrated ecosystem assessments (IEAs) in the context of the wider evolution of IEAs and the science/policy landscape within the ICES region. It looks forward and considers the challenges facing the development of IEAs, specifically those of scoping for objectives, participatory engagement, developing indicators and targets, risk analysis, and creating tools to evaluate management measures for marine anthropogenic activities. It concludes that expectations that the implementation of IEAs will take an ordered, stepwise approach will lead to disappointment and frustration. This is a consequence of the need to operate in an adaptive manner in a complex system. The ecosystem, the science support infrastructure, and the governance systems are all complex. Plus when engaged in a debate about societal objectives, we expect to encounter a complex and changing landscape. As a community, the challenge is to find leverage mechanisms to encourage IEA efforts to provide insights and tools within resources. We will need to innovate and be responsive to the complexity of the ecosystem and governance structures encountered when performing IEA.
Climate variability and change in Ethiopia : exploring impacts and adaptation options for cereal production
Kassie, B.T. - \ 2014
Wageningen University. Promotor(en): Martin van Ittersum, co-promotor(en): R.P. Rötter; Huib Hengsdijk; S. Asseng. - Wageningen : Wageningen University - ISBN 9789461738370 - 183
zea mays - maïs - klimaatverandering - klimaatadaptatie - simulatiemodellen - onzekerheid - ethiopië - zea mays - maize - climatic change - climate adaptation - simulation models - uncertainty - ethiopia
Key words: Climate change, Adaptation, Crop modelling, Uncertainty, Maize (Zea mays), Central Rift Valley.
Smallholder farmers in Ethiopia have been facing severe climate related hazards, in particular highly variable rainfall and severe droughts that negativelyaffect their livelihoods.Anticipated climate change is expected to aggravate some of the existing challenges and impose new risks beyond the range of current experiences. This study aimed at understanding current climate variability and future climate change and associated impacts, and providing insights on current climate risk management strategies and future adaptation options for adapting agriculture, in particular maize production.The study was conducted in the Central Rift Valley, which represents major cereal-based farming systems of the semi-arid environments of Ethiopia. A second case study area, Kobo Valley was also used for additional analysis in part of the study. Empirical statistical analyses, field survey methods, and a systems analytical approach, using field experimental data in combination with crop-climate simulation modelling were used to achieve the objectives of the study.Crop growth simulation modelling was carried out using two well-accepted crop models, which is an innovative feature of the methodology used in this thesis.
The analysis revealed that rainfall exhibited high inter-annual variability (coefficient of variation 15-40%) during the period 1977-2007 in the CRV. The mean annual temperature significantly increased with 0.12 to 0.54 oC per decade during 1977-2007. Projections for future climate suggested that annual rainfall will change by -40 to +10% and the annual temperature is expected to increase in the range of 1.4 to 4.1 oC by 2080s. Simulated water-limited yields are characterized by high inter-annual variability (coefficient of variation 36%) and about 60% of this variability is explained by the variation in growing season rainfall. Actual yields of maize in the CRV are only 28-30% of the simulated water-limited yield. Analysis of climate change scenarios showed that maize yield will decrease on average by 20% in the 2050s relative to a baseline climate due to an increase in temperature and a decrease in growing season rainfall. The negative impact of climate change is very likely, however, the extent of the negative impact has some uncertainties ranging from -2 to -29% depending on crop model and climate change scenario. From the selection of models used, it was concluded that General Circulation Models to assess future climate are the most important source of uncertainty in this study.
In response to perceived impacts, farm households are implementing various coping and adaptation strategies. The most important current adaptive strategies include crop selection, adjusting planting time, in situ moisture conservation and income diversification. Lack of affordable technologies, high costs for agricultural inputs, lack of reliable information on weather forecasts, and insecure land tenure systems were identified as limiting factors of farmers’ adaptive capacity. The crop model-based evaluation of future adaptation options indicates that increasing nitrogen fertilization, use of irrigation and changes in planting dates can compensate for some of the negative impacts of climate change on maize production. Developing more heat tolerant and high yielding new cultivars is critical to sustain crop production under future climate change. It was clear from the study that enabling strategies targeted at agricultural inputs, credit supply, market access and strengthening of local knowledge and information services need to become an integral part of government policies to assist farmers in adapting to the impacts of current climate variability and future climate change.
The socioeconomic vulnerability index: A pragmatic approach for assessing climate-change led risks-A case study in southwestern coastal Bangladesh
Ahsan Bapon, N. ; Warner, J.F. - \ 2014
International Journal of Disaster Risk Reduction 8 (2014). - ISSN 2212-4209 - p. 32 - 49.
adaptive capacity - social vulnerability - multiple stressors - natural hazards - cyclone sidr - adaptation - indicators - framework - level - uncertainty
We develop a Socioeconomic Vulnerability Index (SeVI) for climate change affected communities in seven unions1 of Koyra upazilla 2 in south-western coastal Bangladesh. We survey 60 households from each union to collect data on various vulnerability domains and socioeconomic indicators. The SeVI aggregate these collected data using a composite indicator index, where a relative weight is assigned to each indicator with a view to obtaining weighted average index scores for different vulnerability domains in different unions. Results suggest that southern and south-eastern unions are relatively more vulnerable, which are the most exposed to natural hazards and mostly surrounded by the mangrove forest Sundarbans. Furthermore- social, economic and disaster frequency are found as more influential indicators to adaptive capacity, sensitivity and exposure respectively in Koyra. This pragmatic approach is useful to figure out and monitor socioeconomic vulnerability and/or assess potential adaptation-policy effectiveness in data scarce regions by incorporating scenarios into the SeVI for baseline comparison.
Comparing two sensitivity analysis approaches for two scenarios with a spatially explicit rural agent-based model
Schouten, M.A.H. ; Verwaart, T. ; Heijman, W.J.M. - \ 2014
Environmental Modelling & Software 54 (2014)April. - ISSN 1364-8152 - p. 196 - 210.
land-use - environmental-models - agricultural policies - simulation - biodiversity - schemes - uncertainty - landscapes - management - protocol
In this paper two sensitivity analysis approaches are applied for scenario analysis in a spatially explicit rural agent-based simulation. The simulation aims to assess the socioeconomic and ecological impacts of agricultural policy interventions, market dynamics and environmental change on a regional scale. Two different methods of sensitivity analysis are investigated: i) a one-at-a-time approach where each parameter is varied one after the other, while all other parameters are kept at their nominal values; and ii) a procedure based on Monte Carlo sampling where random sets of input parameter values are related to outputs of the simulation. The complementarity of both approaches and their contribution to the overall interpretation of the model is shown in two scenarios simulating alternative European policy instruments for biodiversity conservation. Results show that a mixed approach of sensitivity analysis leads to a better understanding of the model’s behaviour, and further enhances the description of the simulation’s response to changes in inputs and parameter settings.
Process-based modelling of a headwater catchment in semi-arid conditions: the influence of macropore flow
Schaik, N.L.M.B. ; Bronstert, A. ; Jong, S.M. ; Jetten, V.G. ; Dam, J.C. van; Ritsema, C.J. ; Schnabel, S. - \ 2014
Hydrological Processes 28 (2014)24. - ISSN 0885-6087 - p. 5805 - 5816.
runoff generation - dehesas - uncertainty - management - hydrology - surface - spain
Subsurface stormflow is thought to occur mainly in humid environments with steep terrains. However, in semi-arid areas, preferential flow through macropores can also result in a significant contribution of subsurface stormflow to catchment runoff for varying catchment conditions. Most hydrological models neglect this important subsurface preferential flow. Here, we use the process-oriented hydrological model Hillflow-3D, which includes a macropore flow approach, to simulate rainfall-runoff in the semi-arid Parapuños catchment in Spain, where macropore flow was observed in previous research. The model was extended for this study to account for sorptivity under very dry soil conditions. The results of the model simulations with and without macropore flow are compared. Both model versions give reasonable results for average rainfall situations, although the approach with the macropore concept provides slightly better results. The model results for scenarios of extreme rainfall events (>13.3¿mm¿30¿min-1) however show large differences between the versions with and without macropores. These model results compared with measured rainfall-runoff data show that the model with the macropore concept is better. Our conclusion is that preferential flow is important in controlling surface runoff in case of specific, high intensity rainfall events. Therefore, preferential flow processes must be included in hydrological models where we know that preferential flow occurs. Hydrological process models with a less detailed process description may fit observed average events reasonably well but can result in erroneous predictions for more extreme events.
Assessing and communicating climate change uncertainties : case of the Rhine basin
Pelt, S.C. van - \ 2014
Wageningen University. Promotor(en): Pavel Kabat; Bas Arts; B.J.J.M. van den Hurk. - Wageningen : Wageningen University - ISBN 9789461738332 - 200
waterbeheer - klimaatverandering - onzekerheid - communicatie - risicobeheersing - simulatiemodellen - neerslag - hoogwaterbeheersing - risicoschatting - stroomgebieden - rijn - water management - climatic change - uncertainty - communication - risk management - simulation models - precipitation - flood control - risk assessment - watersheds - river rhine
The main aim of this thesis is to analyse the climate change uncertainties that are important to take into account for long term water management and to explore the communication of these uncertainties. The study design combines natural and social scientific theories and methods and consists of three different elements: 1) an assessment of the dominant uncertainty for changes in mean and extreme precipitation over the Rhine basin; 2) an assessment of the impact of the main uncertainties on changes in flood risk and associated damage in the Rhine basin and 3) an exploration of the use of simulation gaming to communicate about climate change uncertainties to water managers.
Exploring the efficiency of bias corrections of regional climate model output for the assessment of future crop yields in Europe
Bakker, A.M.R. ; Bessembinder, J.J.E. ; Wit, A.J.W. de; Hurk, B.J.J.M. van den; Hoek, S.B. - \ 2014
Regional Environmental Change 14 (2014)3. - ISSN 1436-3798 - p. 865 - 877.
weather generator - global radiation - change scenarios - era-interim - variability - precipitation - projections - simulation - uncertainty - circulation
Excessive summer drying and reduced growing season length are expected to reduce European crop yields in future. This may be partly compensated by adapted crop management, increased CO2 concentration and technological development. For food security, changes in regional to continental crop yield variability may be more important than changes in mean yields. The assessment of changes in regional and larger scale crop variability requires high resolution and spatially consistent future weather, matching a specific climate scenario. Such data could be derived from regional climate models (RCMs), which provide changes in weather patterns. In general, RCM output is heavily biased with respect to observations. Due to the strong nonlinear relation between meteorological input and crop yields, the application of this biased output may result in large biases in the simulated crop yield changes. The use of RCM output only makes sense after sufficient bias correction. This study explores how RCM output can be bias corrected for the assessment of changes in European and subregional scale crop yield variability due to climate change. For this, output of the RCM RACMO of the Royal Netherlands Meteorological Institute was bias corrected and applied within the crop simulation model WOrld FOod STudies to simulate potential and water limited yields of three divergent crops: winter wheat, maize and sugar beets. The bias correction appeared necessary to successfully reproduce the mean yields as simulated with observational data. It also substantially improved the year-to-year variability of seasonal precipitation and radiation within RACMO, but some bias in the interannual variability remained. This is caused by the fact that the applied correction focuses on mean and daily variability. The interannual variability of growing season length, and as a consequence the potential yields too, appeared even deteriorated. Projected decrease in mean crop yields is well in line with earlier studies. No significant change in crop yield variability was found. Yet, only one RCM is analysed in this study, and it is recommended to extend this study with more climate models and a slightly adjusted bias correction taking into account the variability of larger time scales as well
Multimodel assessment of water scarcity under climate change
Schellnhuber, H.J. ; Heinke, J. ; Gerten, D. ; Haddeland, I. ; Arnell, N.W. ; Clark, D.B. ; Dankers, R. ; Eisner, S. ; Kabat, P. - \ 2014
Proceedings of the National Academy of Sciences of the United States of America 111 (2014)9. - ISSN 0027-8424 - p. 3245 - 3250.
future food-production - model description - bias correction - river runoff - resources - availability - vulnerability - uncertainty - scenarios - trends
Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (
Variation in LCA results for disposable polystyrene beverage cups due to multiple data sets and modelling choices
Harst, E.J.M. van der; Potting, J. - \ 2014
Environmental Modelling & Software 51 (2014). - ISSN 1364-8152 - p. 123 - 135.
life-cycle assessment - environmental impacts - uncertainty - ensemble - system
Life Cycle Assessments (LCAs) of the same products often result in different, sometimes even contradictory outcomes. Reasons for these differences include using different data sets and deviating modelling choices. This paper purposely used different data sets and modelling choices to identify how these differences propagated in LCA results. Vehicle for this methodological exploration was an LCA case study of a typical polystyrene (PS) disposable cup. An initial LCA of PS cups was made using only one data set per process. Contribution and sensitivity analysis identified those processes with influential contribution to the overall environmental impact. Next additional data sets were acquired for all influential processes. The spread in impact results for each life cycle process was calculated after impact assessment for each individual inventory data set as to preserve the correlation between inventory data within each individual data set. The spread in impact results reflects uncertainty existing between different data sets for the same process and due to modelling choices. The influence on overall LCA results was quantified by systematically applying all combinations of data sets and modelling choices. Results from the different data sets and modelling choices systematically point to the same processes as main contributors to all impact categories (PS production, cup manufacturing, PS incineration and PS recycling). The spread in toxicity indicators exceeds the energy-related impact categories. Causes of spread are resources and energy used (type, amount, date and origin), reported emissions, and applied allocation procedures. Average LCA results show slight preference for recycling PS compared to incineration in most impact categories. Overlapping spread in results of the two waste treatments, however, does not support the preference for recycling. The approach in this paper showed how variation in data sets and modelling choices propagates in LCA outcomes. This is especially useful for generic LCAs as systematic use of multiple data sets and multiple modelling choices increases the insight in relative contributions of processes to, and uncertainty in the overall LCA. These results might be less easy to perceive, but they provide decision makers with more robust information.
On solving a bi-level stohastic dynamic programming model for analyzing fisheries policies: Fishermen behavior and optimal fish quota
Dijk, D. van; Hendrix, E.M.T. ; Haijema, R. ; Groeneveld, R.A. ; Ierland, E.C. van - \ 2014
Ecological Modelling 272 (2014). - ISSN 0304-3800 - p. 68 - 75.
bioeconomic model - game-theory - management - uncertainty - adjustment - resource - growth - sea
Stochastic dynamic programming (SDP) is a useful tool for analyzing policy questions in fisheries management. In order to understand and reproduce solution procedures such as value function iteration, an analytic elaboration of the problem and model characteristics is required. Because of the increased use of numerical techniques, our aim is to improve the understanding of mathematical properties of the solution procedure and to give more insight into their practical implementation by means of a specific case that uses value function iteration. We provide an analytic description of model characteristics and analyze the solution procedure of a bi-level SDP model to study fisheries policies. At the first level, a policy maker decides on the fish quota to be imposed, keeping in mind fish stock dynamics, capital stock dynamics, long-term resource rents and anticipating fishermen behavior. At the second level, fishermen reveal short-term behavior by reacting on this quota and on current states of fish stock and capital stock by deciding on their investments and fishing effort. An analysis of the behavior of the model is given and a method is elaborated to obtain optimum strategies based on value function iteration. Bi-level decision making enables us to present the model in an understandable manner, and serves as a basis for extension to more complex settings.
Including climate change projections in probabilistic flood risk assessment
Ward, P.J. ; Pelt, S.C. van; Keizer, O. de; Aerts, J.C.J.H. ; Beersma, J.J. ; Hurk, B.J.J.M. van den - \ 2014
Journal of Flood Risk Management 7 (2014)2. - ISSN 1753-318X - p. 141 - 151.
klimaatverandering - overstromingen - risicoschatting - modellen - climatic change - floods - risk assessment - models - rhine basin - model - precipitation - uncertainty - simulations - decisions
This paper demonstrates a framework for producing probabilistic flood risk estimates, focusing on two sections of the Rhine River. We used an ensemble of six (bias-corrected) regional climate model (RCM) future simulations to create a 3000-year time-series through resampling. This was complemented with 12 global climate model (GCM)-based future time-series, constructed by resampling observed time-series of daily precipitation and temperature and modifying these to represent future climate conditions using an advanced delta change approach. We used the resampled time-series as input in the hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV)-96 to simulate daily discharge and extreme discharge quantiles for return periods up to 3000 years. To convert extreme discharges to estimates of flood damage and risk, we coupled a simple inundation model with a damage model. We then fitted probability density functions (PDFs) for the RCM, GCM, and combined ensembles. The framework allows for the assessment of the probability distribution of flood risk under future climate scenario conditions. Because this paper represents a demonstration of a methodological framework, the absolute figures should not be used in decision making at this time.
Evaluating the effect of flood damage-reducing measures: a case study of the unembanked area of Rotterdam, the Netherlands
Moel, H. de; Vliet, M. van; Aerts, J.C.J.H. - \ 2014
Regional Environmental Change 14 (2014)3. - ISSN 1436-3798 - p. 895 - 908.
overstromingen - hoogwaterbeheersing - schade - risicovermindering - risicobeheersing - klimaatverandering - rotterdam - stedelijke gebieden - floods - flood control - damage - risk reduction - risk management - climatic change - rotterdam - urban areas - model - uncertainty - households - insurance - sector - meuse
Empirical evidence of increasing flood damages and the prospect of climatic change has initiated discussions in the flood management community on how to effectively manage flood risks. In the Netherlands, the framework of multi-layer safety (MLS) has been introduced to support this risk-based approach. The MLS framework consists of three layers: (i) prevention, (ii) spatial planning and (iii) evacuation. This paper presents a methodology to evaluate measures in the second layer, such as wet proofing, dry proofing or elevating buildings. The methodology uses detailed land-use data for the area around the city of Rotterdam (up to building level) that has recently become available. The vulnerability of these detailed land-use classes to flooding is assessed using the stage–damage curves from different international models. The methodology is demonstrated using a case study in the unembanked area of Rotterdam in the Netherlands, as measures from the second layer may be particularly effective there. The results show that the flood risk in the region is considerable: EUR 36 million p.a. A large part (almost 60 %) of this risk results from industrial land use, emphasising the need to give this category more attention in flood risk assessments. It was found that building level measures could substantially reduce flood risks in the region because of the relatively low inundation levels of buildings. Risk to residential buildings would be reduced by 40 % if all buildings would be wet-proofed, by 89 % if all buildings would be dry-proofed and elevating buildings over 100 cm would render the risk almost zero. While climate change could double the risk in 2100, such building level measures could easily nullify this effect. Despite the high potential of such measures, actual implementation is still limited. This is partly caused by the lack of knowledge regarding these measures by most Dutch companies and the legal impossibility for municipalities to enforce most of these measures as they would go beyond the building codes established at the national level.
Projected changes in soil organic carbon stocks upon adoption of recommended soil and water conservation practices in the upper Tana river catchment, Kenya
Batjes, N.H. - \ 2014
Land Degradation and Development 25 (2014)3. - ISSN 1085-3278 - p. 278 - 287.
climate-change - land-use - agricultural soils - data requirements - sequestration - management - uncertainty - impacts - world - dynamics
Large areas in the Upper Tana river catchment, Kenya, have been over-exploited, resulting in soil erosion, nutrient depletion and loss of soil organic matter (SOM). This study focuses on sections of the catchment earmarked as being most promising for implementing Green Water Credits, an incentive mechanism to help farmers invest in land and soil management activities that affect all fresh water resources at source. Such management practices can also help restore SOM levels towards their natural level. Opportunities to increase soil organic carbon (SOC) stocks, for two broadly defined land use types (croplands and plantation crops, with moderate input levels), are calculated using a simple empirical model, using three scenarios for the proportion of suitable land that may be treated with these practices (low¿=¿40¿per¿cent, medium¿=¿60¿per¿cent, high¿=¿80¿per¿cent). For the medium scenario, corresponding to implementation on ~348¿000¿ha in the basin, the eco-technologically possible SOC gains are estimated at 4·8 to 9·3¿×¿106¿tonnes (Mg) CO2 over the next 20¿years. Assuming a conservative price of US$10 per tonne CO2-equivalent on the carbon offset market, this would correspond to ~US$48–93 million over a 20-year period of sustained green water management. This would imply a projected (potential) payment of some US$7–13¿ha-1 to farmers annually; this sum would be in addition to incentives that are being put in place for implementing green water management practices and also in addition to the benefits that farmers would realize from the impact on production of these practices themselves
A Protocol for Better Design, Application, and Communication of Population Viability Analyses
Pe'er, G. ; Matsinos, Y.G. ; Johst, K. ; Franz, K.W. ; Turlure, C. ; Radchuk, V. ; Malinowska, A.H. ; Curtis, J.M.R. ; Naujokaitis-Lewis, I. ; Wintle, B.A. ; Henle, K. - \ 2013
Conservation Biology 27 (2013)4. - ISSN 0888-8892 - p. 644 - 656.
management options - biodiversity conservation - environmental-management - dynamic landscapes - density regulation - spotted owl - models - metapopulation - connectivity - uncertainty
Population viability analyses (PVAs) contribute to conservation theory, policy, and management. Most PVAs focus on single species within a given landscape and address a specific problem. This specificity often is reflected in the organization of published PVA descriptions. Many lack structure, making them difficult to understand, assess, repeat, or use for drawing generalizations across PVA studies. In an assessment comparing published PVAs and existing guidelines, we found that model selection was rarely justified; important parameters remained neglected or their implementation was described vaguely; limited details were given on parameter ranges, sensitivity analysis, and scenarios; and results were often reported too inconsistently to enable repeatability and comparability. Although many guidelines exist on how to design and implement reliable PVAs and standards exist for documenting and communicating ecological models in general, there is a lack of organized guidelines for designing, applying, and communicating PVAs that account for their diversity of structures and contents. To fill this gap, we integrated published guidelines and recommendations for PVA design and application, protocols for documenting ecological models in general and individual-based models in particular, and our collective experience in developing, applying, and reviewing PVAs. We devised a comprehensive protocol for the design, application, and communication of PVAs (DAC-PVA), which has 3 primary elements. The first defines what a useful PVA is; the second element provides a workflow for the design and application of a useful PVA and highlights important aspects that need to be considered during these processes; and the third element focuses on communication of PVAs to ensure clarity, comprehensiveness, repeatability, and comparability. Thereby, DAC-PVA should strengthen the credibility and relevance of PVAs for policy and management, and improve the capacity to generalize PVA findings across studies.