Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    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.
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