Modelling food security : Bridging the gap between the micro and the macro scale
Müller, Birgit ; Hoffmann, Falk ; Heckelei, Thomas ; Müller, Christoph ; Hertel, Thomas W. ; Polhill, J.G. ; Wijk, Mark van; Achterbosch, Thom ; Alexander, Peter ; Brown, Calum ; Kreuer, David ; Ewert, Frank ; Ge, Jiaqi ; Millington, James D.A. ; Seppelt, Ralf ; Verburg, Peter H. ; Webber, Heidi - \ 2020
Global environmental change : human and policy dimensions 63 (2020). - ISSN 0959-3780
Agent-based models - Crop models - Economic equilibrium models - Food security - Land use - Model integration - Multi-scale interactions - Social-ecological feedbacks
Achieving food and nutrition security for all in a changing and globalized world remains a critical challenge of utmost importance. The development of solutions benefits from insights derived from modelling and simulating the complex interactions of the agri-food system, which range from global to household scales and transcend disciplinary boundaries. A wide range of models based on various methodologies (from food trade equilibrium to agent-based) seek to integrate direct and indirect drivers of change in land use, environment and socio-economic conditions at different scales. However, modelling such interaction poses fundamental challenges, especially for representing non-linear dynamics and adaptive behaviours. We identify key pieces of the fragmented landscape of food security modelling, and organize achievements and gaps into different contextual domains of food security (production, trade, and consumption) at different spatial scales. Building on in-depth reflection on three core issues of food security – volatility, technology, and transformation – we identify methodological challenges and promising strategies for advancement. We emphasize particular requirements related to the multifaceted and multiscale nature of food security. They include the explicit representation of transient dynamics to allow for path dependency and irreversible consequences, and of household heterogeneity to incorporate inequality issues. To illustrate ways forward we provide good practice examples using meta-modelling techniques, non-equilibrium approaches and behavioural-based modelling endeavours. We argue that further integration of different model types is required to better account for both multi-level agency and cross-scale feedbacks within the food system.
|Transities door small wins
Termeer, C.J.A.M. ; Dewulf, A.R.P.J. - \ 2019
In: Meer dan de som der delen / Kessener, Brechtje, van Oss, Leike, Management impact - ISBN 9789462762596 - p. 677 - 693.
Onze samenleving heeft in toenemende mate te maken met weerbarstige vraagstukken zoals klimaatverandering, terreur, armoede, biodiversiteit, duurzame mobiliteit of voedselzekerheid. Dit type vraagstukken wordt ook wel aangeduid als 'wicked problems' (Rittel & Webber, 1973) of taai vraagstukken (Vermaak, 2009). Ze vertonen een aantal kenmerken waardoor ze bijzonder uitdagend zijn, zoals betrokkenheid van actoren met conflicterende waarden en doelen, problemen die regelmatig van gedaante veranderen onder invloed van interventies en autonome dynamiek, problemen die het symptoon zijn van andere problemen op een andere plek of schaalniveau en oplossingen van vandaag die leiden tot het probleem van morgen. Bovendien kennen wicked problems geen stopregel: het is nooit klaar en het kan altijd beter (Head & Afford, 2015).
Global wheat production with 1.5 and 2.0°C above pre‐industrial warming
Liu, B. ; Martre, P. ; Ewert, F. ; Porter, J.R. ; Challinor, A.J. ; Muller, G. ; Ruane, A.C. ; Waha, K. ; Thorburn, Peter J. ; Aggarwal, P.K. ; Ahmed, M. ; Balkovic, Juraj ; Basso, B. ; Biernath, C. ; Bindi, M. ; Cammarano, D. ; Sanctis, Giacomo De; Dumont, B. ; Espadafor, M. ; Eyshi Rezaei, Ehsan ; Ferrise, Roberto ; Garcia-Vila, M. ; Gayler, S. ; Gao, Y. ; Horan, H. ; Hoogenboom, G. ; Izaurralde, Roberto C. ; Jones, C.D. ; Kassie, Belay T. ; Kersebaum, K.C. ; Klein, C. ; Koehler, A.K. ; Maiorano, Andrea ; Minoli, Sara ; Montesino San Martin, M. ; Kumar, S.N. ; Nendel, C. ; O'Leary, G.J. ; Palosuo, T. ; Priesack, E. ; Ripoche, D. ; Rötter, R.P. ; Semenov, M.A. ; Stockle, Claudio ; Streck, T. ; Supit, I. ; Tao, F. ; Velde, M. van der; Wallach, D. ; Wang, E. ; Webber, H. ; Wolf, J. ; Xiao, L. ; Zhang, Z. ; Zhao, Z. ; Zhu, Y. ; Asseng, S. - \ 2019
Global Change Biology 25 (2019)4. - ISSN 1354-1013 - p. 1428 - 1444.
Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5°C and 2.0°C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5 °C scenario and -2.4% to 10.5% under the 2.0 °C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer -India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production are therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.
Protocol-based storylines for integrated assessments of future European agriculture
Mitter, H. ; Schönhart, M. ; Sinabell, Franz ; Techen, A.K. ; Helming, K. ; Bodirsky, B. ; Holman, I. ; Kok, K. ; Lehtonen, H. ; Leip, A. ; Lotze-Campen, H. ; Mathijs, E. ; Mehdi, B. ; Michetti, M. ; Mittenzwei, K. ; Oygarden, Lilian ; Priess, J. ; Reidsma, P. ; Schaldach, R. ; Schmid, E. ; Webber, H. - \ 2018
In: Methoden für eine evidenzbasierte Agrarpolitik - Erfahrungen, Bedarf und Entwicklungen Methods for an evidence-based agricultural policy - Experiences, demand and new developments. - ÖGA - p. 121 - 122.
Integrated assessments in agriculture often necessitate storylines to define socio-economic framework assumptions. They are available at global to continental scales but their spatial resolution and scope is insufficient for sectoral studies in agriculture at national to regional scales. We therefore aim at developing protocol-based storylines for European agriculture by extending and enriching global storylines. Consistency across spatial scales and sectors related to agriculture are maintained by following a nested approach. Stakeholders contribute to the research process in order to ensure usefulness and usability of the results. We present the innovative research design to generate storylines for European agriculture and give examples of storyline elements. The shared protocol increases transparency of how storyline elements are identified, prioritized and combined, improving comparability and consistency of integrated assessments within and across scales.
Circumpolar Arctic Vegetation Classification
Walker, Donald A. ; Daniëls, Fred J.A. ; Matveyeva, Nadezhda V. ; Šibík, Jozef ; Walker, Marilyn D. ; Breen, Amy L. ; Druckenmiller, Lisa A. ; Raynolds, Martha K. ; Bültmann, Helga ; Hennekens, Stephan ; Buchhorn, Marcel ; Epstein, Howard E. ; Ermokhina, Ksenia ; Fosaa, Anna M. ; Heidmarsson, Starri ; Heim, Birgit ; Jónsdóttir, Ingibjörg S. ; Koroleva, Natalia ; Lévesque, Esther ; MacKenzie, William H. ; Henry, Greg H.R. ; Nilsen, Lennart ; Peet, Robert ; Razzhivin, Volodya ; Talbot, Stephen S. ; Telyatnikov, Mikhail ; Thannheiser, Dietbert ; Webber, Patrick J. ; Wirth, Lisa M. - \ 2018
Phytocoenologia 48 (2018)2. - ISSN 0340-269X - p. 181 - 201.
Alaska - Bioclimate gradient - Braun-Blanquet approach - Habitat type - Plant growth form - Plot database - Syntaxon - Tundra - Vegetation mapping
Aims: An Arctic Vegetation Classification (AVC) is needed to address issues related to rapid Arctic-wide changes to climate, land-use, and biodiversity. Location: The 7.1 million km2 Arctic tundra biome. Approach and conclusions: The purpose, scope and conceptual framework for an Arctic Vegetation Archive (AVA) and Classification (AVC) were developed during numerous workshops starting in 1992. The AVA and AVC are modeled after the European vegetation archive (EVA) and classification (EVC). The AVA will use Turboveg for data management. The AVC will use a Braun-Blanquet (Br.-Bl.) classification approach. There are approximately 31,000 Arctic plots that could be included in the AVA. An Alaska AVA (AVA-AK, 24 datasets, 3026 plots) is a prototype for archives in other parts of the Arctic. The plan is to eventually merge data from other regions of the Arctic into a single Turboveg v3 database. We present the pros and cons of using the Br.-Bl. classification approach compared to the EcoVeg (US) and Biogeoclimatic Ecological Classification (Canada) approaches. The main advantages are that the Br.-Bl. approach already has been widely used in all regions of the Arctic, and many described, well-accepted vegetation classes have a pan-Arctic distribution. A crosswalk comparison of Dryas octopetala communities described according to the EcoVeg and the Braun-Blanquet approaches indicates that the non-parallel hierarchies of the two approaches make crosswalks difficult above the plantcommunity level. A preliminary Arctic prodromus contains a list of typical Arctic habitat types with associated described syntaxa from Europe, Greenland, western North America, and Alaska. Numerical clustering methods are used to provide an overview of the variability of habitat types across the range of datasets and to determine their relationship to previously described Braun-Blanquet syntaxa. We emphasize the need for continued maintenance of the Pan-Arctic Species List, and additional plot data to fully sample the variability across bioclimatic subzones, phytogeographic regions, and habitats in the Arctic. This will require standardized methods of plot-data collection, inclusion of physiogonomic information in the numeric analysis approaches to create formal definitions for vegetation units, and new methods of data sharing between the AVA and national vegetation- plot databases.
Isolation by oceanic distance and spatial genetic structure in an overharvested international fishery
Truelove, Nathan K. ; Box, Stephen J. ; Aiken, Karl A. ; Blythe-Mallett, Azra ; Boman, Erik M. ; Booker, Catherine J. ; Byfield, Tamsen T. ; Cox, Courtney E. ; Davis, Martha H. ; Delgado, Gabriel A. ; Glazer, Bob A. ; Griffiths, Sarah M. ; Kitson-Walters, Kimani ; Kough, Andy S. ; Pérez Enríquez, Ricardo ; Preziosi, Richard F. ; Roy, Marcia E. ; Segura-García, Iris ; Webber, Mona K. ; Stoner, Allan W. - \ 2017
Diversity and Distributions 23 (2017)11. - ISSN 1366-9516 - p. 1292 - 1300.
Connectivity - Conservation - Dispersal - Fisheries - Genetics - Spatial
Aim: A detailed understanding of spatial genetic structure (SGS) and the factors driving contemporary patterns of gene flow and genetic diversity are fundamental for developing conservation and management plans for marine fisheries. We performed a detailed study of SGS and genetic diversity throughout the overharvested queen conch (Lobatus gigas) fishery. Caribbean countries were presented as major populations to examine transboundary patterns of population differentiation. Location: Nineteen locations in the greater Caribbean from Anguilla, the Bahamas, Belize, Caribbean Netherlands, Honduras, Jamaica, Mexico, Turks and Caicos, and the USA. Methods: We genotyped 643 individuals with nine microsatellites. Population genetic and multivariate analyses characterized SGS. We tested the alternate hypotheses: (1) SGS is randomly distributed in space or (2) pairwise genetic structure among sites is correlated with oceanic distance (IBOD). Results: Our study found that L. gigas does not form a single panmictic population in the greater Caribbean. Significant levels of genetic differentiation were identified between Caribbean countries (FCT = 0.011; p = .0001), within Caribbean countries (FSC = 0.003; p = .001), and among sites irrespective of geographic location (FST = 0.013; p = .0001). Gene flow across the greater Caribbean was constrained by oceanic distance (p = .0009; Mantel r = .40), which acted to isolate local populations. Main conclusions: Gene flow over the spatial scale of the entire Caribbean basin is constrained by oceanic distance, which may impede the natural recovery of overfished L. gigas populations. Our results suggest a careful blend of local and international management will be required to ensure long-term sustainability for the species.
Climate change impacts on crop yields, land use and environment in response to crop sowing dates and thermal time requirements
Zimmermann, Andrea ; Webber, Heidi ; Zhao, Gang ; Ewert, Frank ; Kros, Hans ; Wolf, Joost ; Britz, Wolfgang ; Vries, Wim de - \ 2017
Agricultural Systems 157 (2017). - ISSN 0308-521X - p. 81 - 92.
Climate change - Crop management - Europe - Integrated assessment
Impacts of climate change on European agricultural production, land use and the environment depend on its impact on crop yields. However, many impact studies assume that crop management remains unchanged in future scenarios, while farmers may adapt their sowing dates and cultivar thermal time requirements to minimize yield losses or realize yield gains. The main objective of this study was to investigate the sensitivity of climate change impacts on European crop yields, land use, production and environmental variables to adaptations in crops sowing dates and varieties' thermal time requirements. A crop, economic and environmental model were coupled in an integrated assessment modelling approach for six important crops, for 27 countries of the European Union (EU27) to assess results of three SRES climate change scenarios to 2050. Crop yields under climate change were simulated considering three different management cases; (i) no change in crop management from baseline conditions (NoAd), (ii) adaptation of sowing date and thermal time requirements to give highest yields to 2050 (Opt) and (iii) a more conservative adaptation of sowing date and thermal time requirements (Act). Averaged across EU27, relative changes in water-limited crop yields due to climate change and increased CO2 varied between − 6 and + 21% considering NoAd management, whereas impacts with Opt management varied between + 12 and + 53%, and those under Act management between − 2 and + 27%. However, relative yield increases under climate change increased to + 17 and + 51% when technology progress was also considered. Importantly, the sensitivity to crop management assumptions of land use, production and environmental impacts were less pronounced than for crop yields due to the influence of corresponding market, farm resource and land allocation adjustments along the model chain acting via economic optimization of yields. We conclude that assumptions about crop sowing dates and thermal time requirements affect impact variables but to a different extent and generally decreasing for variables affected by economic drivers.
|Recent advances in integrated assessments of climate change impacts on European agriculture
Webber, Heidi ; Reidsma, P. ; Ewert, Frank - \ 2017
In: Book of abstracts. - - p. 38 - 38.
The broad EU public expects agriculture to improve global food security, protect the environment and sustain rural communities and landscapes. Agricultural policy makers must additionally consider resource scarcity and degradation, loss of biodiversity, climate change adaptation and, increasingly, mitigation. Integrated assessment modelling (IAM) can simultaneously consider key
agricultural drivers and the main economic and environmental outcomes in identifying opportunities and balancing trade-offs for EU agriculture in the future. In this review of recent and on-going European scale IAM studies, results are synthesized to quantify the range of uncertainty for key impact variables. Explicit attention is given to the drivers (climate change, socio-economic scenarios, technological) and adaptations considered, their relative importance
across impact variables, feedbacks and cross-scale linkages. Crop management adaptations, widely demonstrated in regional studies, were found to have a large effect on crop yields as simulated with crop models, with relatively less influence on simulated economic variables. The few studies to simultaneously consider climate change and technological development, found yield trends offset yield losses due to climate change and be more important than adaptation.
The MACSUR Coordinate Global and Regional Assessment (CGRA) seeks to explicitly model yields trends with crop models, partnering with the Global Yield Gap Atlas (GYGA) to understand the relative contribution of management and breeding to past trends. Examples of heat and drought risk analysis with crop models are presented, though their consideration in economic studies
remains limited. Finally, opportunities are identified for cross-scale analysis and assessment within MACSUR.
Modeling crops from genotype to phenotype in a changing climate
Martre, Pierre ; Yin, Xinyou ; Ewert, Frank - \ 2017
Field Crops Research 202 (2017). - ISSN 0378-4290 - p. 1 - 4.
Climate change is exerting daunting challenges to world agriculture. Several studies have shown that modern crop cultivars are not well adapted to the recent climate changes (Brisson et al., 2010; Oury et al., 2012). Crop models are potentially able to capture crop genotype-to-phenotype relationships. They are hence a helpful tool to identify and assess the effectiveness of improved crop traits and to support the efficiency of plant breeding programs (Messina et al., 2009; Martre et al., 2014; Hammer et al., 2016). A recent compilation of studies (Yin and Struik, 2016) described some of the progress in combining crop modelling and genetics but it also recognized that current crop models need upgrading. This special issue aims to contribute to the further development of this research area with a particular focus on crops grown under a changing climate. It presents results of a workshop of the Wheat team (https://www. agmip.org/s/wheat/) of The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) and of the Expert Working Group on Wheat Plant and Crop Modeling of the Wheat Initiative (http://www.wheatinitiative.org/activities/ expert-working-groups/wheat-plant-and-crop-modelling) in 2014 at INRA Clermont-Ferrand, France, and includes also invited papers. The contributions cover three main areas. 1. Improving crop growth models to account for climate change impacts Several recent papers (e.g. Rötter et al., 2011; Boote et al., 2013; Ewert et al., 2015), have discussed the need for an upgrading of current crop models to efficiently project the growth of crops under conditions that will more often be encountered in future climates, with higher temperature, more frequent heat spells, more severe and longer periods of drought, or flooding. To improve crop models , an important step are model inter-comparison studies, which requires a level of international coordination that has only recently been made possible by AgMIP, and in Europe by the project on Modelling European Agriculture with Climate Change for Food Security of the Joint Research Programming Initiative on Agriculture, Food Security and Climate Change (http://macsur.eu/). Two papers in this special issue report results from such concerted research actions. Maiorano et al. (2017) present the first concerted crop model improvement study following up on recent wheat model intercomparison exercises (Asseng et al., 2013; Asseng et al., 2015; Martre et al., 2015; Cammarano et al., 2016), where 15 models were improved for predicting the impact of high temperature on wheat crop growth and yield. The authors show that the improvement of individual model skills translates into a reduced uncertainty of the multi-model ensemble prediction and in a reduction by half of the number of models which are needed in a multi-model ensemble to stay within acceptable uncertainty range. Heat stress signals are in the form of absolute temperature thresholds above which the formation of reproductive sink (Alghabari et al., 2014; Prasad and Djanaguiraman, 2014) or leaf senescence (Zhao et al., 2007) could be adversely affected. Under warm conditions the air and surface temperatures can differ by more than 10 • C (Siebert et al., 2014) and heat stress effect on sink formation or leaf senescence are likely determined by tissue or canopy temperature (Eyshi Rezaei et al., 2015). It may thus be more important to consider the organ or canopy temperature as the driving variable of crops to heat stress rather than air temperature as typically used by most crop models so far. But how good are current crop models to predict canopy temperature? What is the importance of considering canopy temperature to simulate the impact of heat stress on grain yield formation? These questions were addressed by Webber et al. (2017), who evaluated nine wheat crop models that implement different mechanistic or empirical algorithms to calculate canopy temperature. The models varied widely in their ability to simulate measured canopy temperature and in general had better predictions of yield when calculated canopy temperature was used to model the effect of heat stress on processes determining grain yield but the improvement was relatively small. Several studies have previously suggested that the level of sink limitation of yield formation may significantly increase under future climate. Shi et al. (2017) studied the effect of high night temperature on rice yield formation under different levels of nitrogen supply. They used a novel modeling approach to quantify source–sink relationships during the grain filling period and showed that increased nitrogen application does not alleviate the impact of high night temperature on source-sink interactions across cultivars and seasons (water supply). However, genetic differences in the tolerance to high night temperature appeared to be related to genetic differences in sink size. Transparent evaluation of crop models with detailed field studies is an important aspect of model improvement that helps to set the limits of the conditions under which a given model can be used with enough confidence and to identify aspects where improvements are needed. Asseng et al. (2017) used field experiments with modified sink–source relationships to explore how the Nwheat crop model respond to such modifications. The authors show that their model is able to reproduce several experimental treatments with reduced source (e.g. crop shading) or sink (e.g. ear halving) but they also identify deficiencies in simulating grain set and final grain size, point to areas http://dx. where Nwheat, and most likely other wheat and cereal models, need improvement. 2. Modeling the response of genotypes to the environment More than two decades ago researchers have started to emphasize the potential role that crop models could play for crop improvement (Shorter et al., 1991). Since then important milestones have been reached with the use of crop models to characterize breeding and production environments (e.g. Chenu et al., 2013; Harrison et al., 2014), the development of QTL-based models (e.g. Quilot et al., 2005; Yin et al., 2005; Zheng et al., 2013), and more recently the link of crop models with genomic prediction models (e.g. Heslot et al., 2014; Technow et al., 2015). Several articles in this special issue contribute to the advancement of genotype to phenotype modelling. Most underrepresented so far are studies that aim to link crop system models with understandings of gene action at the molecular level. In this special issue Chew et al. (2017) present such an effort in the model species Arabidopsis thaliana and discuss avenues to further extend on cross-disciplinary work for crop species. The type of models presented by Chew and coworkers represent a new step in integrating knowledge across biological scales with significant potential to contribute to crop improvement. Uptmoor et al. (2017) combined a genome-wide prediction model with a process-based flowering time model to predict the heading time of the progeny of a barley population in independent environments. Rice, like several other cereal species, shows large adaptive phenotypic plasticity enabling yield stability across environments. Such plasticity is often observed between tiller production and pan-icle size. In their paper Kumar et al. (2017) report on the plasticity of organ size and number of 12 high-yielding rice genotypes of high and low tillering plant types. They show that most of the observed genetic variations in morphological and yield component traits can be predicted by the rice model SAMARA and discuss the possibility offered by such a type of process-based models to predict the response of new ideotypes to changing environments and crop management practices. Gouache et al. (2017) used a modified version of the phenology module of the wheat model ARCWHEAT parametrized for hundreds of genotypes to analyze the possibilities to adapt wheat to future growing conditions in France. Their results suggest that the beginning of stem extension can be advanced by several weeks without significant risk of frost damage and that photoperiod insensitive PpdD1 and spring type Vrn3 allele combinations are undesirable. The authors discuss the need, in addition to crop modeling, to use available knowledge in crop physiology and of the allelic variability at the loci underpinning important traits in gene pools to implement breeding ideotypes in commercial improvement programs. Global simulation studies usually do not consider the adaptation of cultivars to regional or sub-regional climate, soil properties, and crop management practices, which limits our capacity to analyze the impacts of growing conditions on food security. Gbegbelegbe et al. (2017) calibrated the wheat crop model CROPSIM-CERES for modern high-yielding cultivars adapted to the 17 CIMMYT wheat mega environments. Their results show that the use of ex-ante calibrated region-specific cultivars improves significantly the model skills for predicting grain yield at country level. This study is an important step to reduce the uncertainty of the projections of regional and global wheat production to enable advanced studies on food security to address questions related to the impact of genetic improvement and agricultural technology with climate change. Comprehensive model testing is often a neglected aspect to identify model strengths and deficiencies. Raymundo et al. (2017) present a comprehensive field testing of the SUBSTOR-potato model with experiments carried out in 19 countries. They show that while tuber yield is in general well simulated, for different potato species and cultivars, the response of the model to elevated atmospheric CO 2 concentration and high temperature needs to be improved before it can be used to project the impact of climate change and discussed how its skills can be enhanced. 3. Modelling the impact of climate change on grains and seeds quality Studies of the impact of climate change on food security issues have essentially focused on crop production, while nutritional and functional quality aspects of grains have received limited attention (Müller et al., 2014). This is at least partly due to the limited capability of most crop models which are typically restricted to predicting average grain size and protein or oil concentration (Martre et al., 2011). In this special issue Nuttall et al. (2017) review the current knowledge of the response on wheat grain functional properties to high temperature and elevated atmospheric CO 2 concentration. The authors also discuss how the capability of wheat crop models to consider quality aspects can be advanced and provide a conceptual framework to model the size distribution of gluten proteins and grain distribution using a single spike approach. The rise in global temperature is also a concern for sunflower quality. High oleic sunflower hybrids are increasingly grown worldwide as their higher content in unsaturated fatty acids compared with traditional hybrids increases the storage life of oil and because of the potent hypocholesterolemic effect of unsaturated fatty acids. However, the percentage of oleic acids in the oil decreases under warmer night temperatures (Aguirrezábal et al., 2014). Here, Angeloni et al. (2017) explored the response of sunflower phenol-ogy and seed oleic acid percentage to temperature for high oleic hybrids of sunflower grown in a network of field experiments in the argentine sunflower growing regions. The authors used these information to calibrate a sunflower model and to project the impact of a future global warming scenario on oil oleic percentage at different sites with different sowing dates. Their results provide important information to optimize the conditions to phenotype for high oleic percentage in both controlled and conditions field, and identifies traits on which breeders should focus to improve oil quality in the future. In summary, this special issue presents promising advances in modeling the improvement of crop species under climate change and future growing conditions. They represent significant efforts to reduce model uncertainty to improve confidence in using crop models in climate change impact studies to support the breeding of genotypes better adapted to future growing conditions. Much more research will be required and we hope that the publication of this special issue will catalyze more activities in this emerging research area.
The Alaska Arctic Vegetation Archive (AVA-AK)
Walker, Donald A. ; Breen, Amy L. ; Druckenmiller, Lisa A. ; Wirth, Lisa W. ; Fisher, Will ; Raynolds, Martha K. ; Šibík, Jozef ; Walker, Marilyn D. ; Hennekens, Stephan ; Boggs, Keith ; Boucher, Tina ; Buchhorn, Marcel ; Bültmann, Helga ; Cooper, David J. ; Daniëls, Fred J.A. ; Davidson, Scott J. ; Ebersole, James J. ; Elmendorf, Sara C. ; Epstein, Howard E. ; Gould, William A. ; Hollister, Robert D. ; Iversen, Colleen M. ; Jorgenson, M.T. ; Kade, Anja ; Lee, Michael T. ; MacKenzie, William H. ; Peet, Robert K. ; Peirce, Jana L. ; Schickhoff, Udo ; Sloan, Victoria L. ; Talbot, Stephen S. ; Tweedie, Craig E. ; Villarreal, Sandra ; Webber, Patrick J. ; Zona, Donatella - \ 2016
Phytocoenologia 46 (2016)2. - ISSN 0340-269X - p. 221 - 229.
Circumpolar - Cluster analysis - Database - Tundra - Turboveg - Vegetation classification
The Alaska Arctic Vegetation Archive (AVA-AK, GIVD-ID: NA-US-014) is a free, publically available database archive of vegetation-plot data from the Arctic tundra region of northern Alaska. The archive currently contains 24 datasets with 3,026 non-overlapping plots. Of these, 74% have geolocation data with 25-m or better precision. Species cover data and header data are stored in a Turboveg database. A standardized Pan Arctic Species List provides a consistent nomenclature for vascular plants, bryophytes, and lichens in the archive. A web-based online Alaska Arctic Geoecological Atlas (AGA-AK) allows viewing and downloading the species data in a variety of formats, and provides access to a wide variety of ancillary data. We conducted a preliminary cluster analysis of the first 16 datasets (1,613 plots) to examine how the spectrum of derived clusters is related to the suite of datasets, habitat types, and environmental gradients. We present the contents of the archive, assess its strengths and weaknesses, and provide three supplementary files that include the data dictionary, a list of habitat types, an overview of the datasets, and details of the cluster analysis.
Cross-Sector Partnerships and the Co-creation of Dynamic Capabilities for Stakeholder Orientation
Dentoni, D. ; Bitzer, V.C. ; Pascucci, S. - \ 2016
Journal of Business Ethics 135 (2016)1. - ISSN 0167-4544 - p. 35 - 53.
This paper explores the relationship between business experience in cross-sector partnerships (CSPs) and the co-creation of what we refer to as ‘dynamic capabilities for stakeholder orientation,’ consisting of the four dimensions of (1) sensing, (2) interacting with, (3) learning from and (4) changing based on stakeholders. We argue that the co-creation of dynamic capabilities for stakeholder orientation is crucial for CSPs to create societal impact, as stakeholder-oriented organizations are more suited to deal with “wicked problems,” i.e., problems that are large, messy, and complex (Rittel and Webber, Policy Sciences 4:155–169, 1973; Waddock, Paper presented at the 3rd international symposium on cross sector social interactions, 2012). By means of a grounded theory approach of inductive research, we collected and interpreted data on four global agri-food companies which have heterogeneous experience in participating in CSPs. The results of this paper highlight that only companies’ capability of interacting with stakeholders continually increases, while their capabilities of sensing, learning from, and changing based on stakeholders first increase and then decrease as companies gain more experience in CSP participation. To a large extent, this can be attributed to the development of corporate strategies on sustainability after a few years of CSP participation, which entails a shift from a reactive to a proactive attitude towards sustainability issues and which may decrease the need or motivation for stakeholder orientation. These findings open up important issues for discussion and for future research on the impact of CSPs in a context of wicked problems.
The implication of irrigation in climate change impact assessment : A European-wide study
Zhao, Gang ; Webber, Heidi ; Hoffmann, Holger ; Wolf, Joost ; Siebert, Stefan ; Ewert, Frank - \ 2015
Global Change Biology 21 (2015)11. - ISSN 1354-1013 - p. 4031 - 4048.
Climate change - CO effects - Crop model - Irrigation - LINTUL - SIMPLACE - Water availability - Yield change
This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO2 effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982-2006) and three SRES scenarios (B1, B2 and A1B, 2040-2064) under rainfed and irrigated conditions, using a process-based crop model, SIMPLACE . We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr-1). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO2 effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO2 effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area.
Climate change impacts on European crop yields: Do we need to consider nitrogen limitation?
Webber, Heidi ; Zhao, G. ; Wolf, J. ; Britz, W. ; Vries, W.D. ; Gaiser, T. ; Hoffmann, H. ; Ewert, F. - \ 2015
European Journal of Agronomy 71 (2015). - ISSN 1161-0301 - p. 123 - 134.
Global climate impact studies with crop models suggest that including nitrogen and water limitation causes greater negative climate change impacts on actual yields compared to water-limitation only. We simulated water limited and nitrogen-water limited yields across the EU-27 to 2050 for six key crops with the SIMPLACE model to assess how important consideration of nitrogen limitation is in climate impact studies for European cropping systems. We further investigated how crop nitrogen use may change under future climate change scenarios. Our results suggest that inclusion of nitrogen limitation hardly changed crop yield response to climate for the spring-sown crops considered (grain maize, potato, and sugar beet). However, for winter-sown crops (winter barley, winter rapeseed and winter wheat), simulated impacts to 2050 were more negative when nitrogen limitation was considered, especially with high levels of water stress. Future nitrogen use rates are likely to decrease due to climate change for spring-sown crops, largely in parallel with their yields. These results imply that climate change impact studies for winter-sown crops should consider N-fertilization. Specification of future N fertilization rates is a methodological challenge that is likely to need integrated assessment models to address.
Combined analysis of climate, technological and price changes on future arable farming systems in Europe
Wolf, J. ; Kanellopoulos, Argyris ; Kros, J. ; Webber, H. ; Zhao, G. ; Britz, W. ; Reinds, G.J. ; Ewert, F. ; Vries, W. de - \ 2015
Agricultural Systems 140 (2015). - ISSN 0308-521X - p. 56 - 73.
In this study, we compare the relative importance of climate change to technological, management, price and policy changes on European arable farming systems. This required linking four models: the SIMPLACE crop growth modelling framework to calculate future yields under climate change for arable crops; the CAPRI model to estimate impacts on global agricultural markets, specifically product prices; the bio-economic farm model FSSIM to calculate the future changes in cropping patterns and farm net income at the farm and regional level; and the environmental model INTEGRATOR to calculate nitrogen (N) uptake and losses to air and water. First, the four linked models were applied to analyse the effect of climate change only or a most likely baseline (i.e. B1) scenario for 2050 as well as for two alternative scenarios with, respectively, strong (i.e. A1-b1) and weak economic growth (B2) for five regions/countries across Europe (i.e. Denmark, Flevoland, Midi Pyrenées, Zachodniopomorski and Andalucia). These analyses were repeated but assuming in addition to climate change impacts, also the effects of changes in technology and management on crop yields, the effects of changes in prices and policies in 2050, and the effects of all factors together. The outcomes show that the effects of climate change to 2050 result in higher farm net incomes in the Northern and Northern-Central EU regions, in practically unchanged farm net incomes in the Central and Central-Southern EU regions, and in much lower farm net incomes in Southern EU regions compared to those in the base year. Climate change in combination with improved technology and farm management and/or with price changes towards 2050 results in a higher to much higher farm net incomes. Increases in farm net income for the B1 and A1-b1 scenarios are moderately stronger than those for the B2 scenario, due to the smaller increases in product prices and/or yields for the B2 scenario. Farm labour demand slightly to moderately increases towards 2050 as related to changes in cropping patterns. Changes in N2O emissions and N leaching compared to the base year are mainly caused by changes in total N inputs from the applied fertilizers and animal manure, which in turn are influenced by changes in crop yields and cropping patterns, whereas NH3 emissions are mainly determined by assumed improvements in manure application techniques. N emissions and N leaching strongly increase in Denmark and Zachodniopomorski, slightly decrease to moderately increase in Flevoland and Midi-Pyrenées, and strongly decrease in Andalucia, except for NH3 emissions which zero to moderately decrease in Flevoland and Denmark.
Crop modelling for integrated assessment of risk to food production from climate change
Ewert, F. ; Rötter, R.P. ; Bindi, M. ; Webber, Heidi ; Trnka, M. ; Kersebaum, K.C. ; Olesen, J.E. ; Ittersum, M.K. van; Janssen, S.J.C. ; Rivington, M. ; Semenov, M.A. ; Wallach, D. ; Porter, J.R. ; Stewart, D. ; Verhagen, J. ; Gaiser, T. ; Palosuo, T. ; Tao, F. ; Nendel, C. ; Roggero, P.P. ; Bartosová, L. ; Asseng, S. - \ 2015
Environmental Modelling & Software 72 (2015). - ISSN 1364-8152 - p. 287 - 303.
The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches.
The impact of domestic energy efficiency retrofit schemes on householder attitudes and behaviours
Long, T.B. ; Young, W. ; Webber, P. ; Gouldson, A. ; Harwatt, H. - \ 2015
Journal of Environmental Planning and Management 58 (2015)10. - ISSN 0964-0568 - p. 1853 - 1876.
sustainable consumption - uk households - cold homes - conservation - policy - strategies - spillover - barriers - savings - agenda
Retrofitting existing housing stock to improve energy efficiency is often required to meet climate mitigation, public health and fuel poverty targets. Increasing uptake and effectiveness of retrofit schemes requires understanding of their impacts on householder attitudes and behaviours. This paper reports results of a survey of 500 Kirklees householders in the UK, where the Kirklees Warm Zone scheme took place. This was a local government led city scale domestic retrofit programme that installed energy efficiency measures at no charge in over 50,000 houses. The results highlight key design features of the scheme, socio-economic and attitudinal factors that affected take-up of energy efficiency measures and impacts on behaviour and energy use after adoption. The results emphasise the role that positive feedback plays in reinforcing pro-environmental attitudes and behaviours of participants and in addressing concerns of non-participants. Our findings have implications for the design and operation of future domestic energy efficiency retrofit schemes.
|Improvement of the use and contents of tools for policy relevant test cases: Agri Test case
Vries, W. de; Kros, H. ; Reinds, G.J. ; Webber, H. ; Enders, A. ; Zhao, G. ; Britz, W. ; Ewert, F. ; Wolf, J. ; Kanellopoulos, A. ; Ittersum, M.K. van - \ 2014
EU - 71 p.
Wicked problems and clumsy solutions: Planning as expectation management
Hartmann, Thomas - \ 2012
Planning Theory 11 (2012)3. - ISSN 1473-0952 - p. 242 - 256.
complexity - expectation management - participation - polyrationality - uncertainty
In 1973, Horst W Rittel and Malvin A Webber introduced the term 'wicked problem' in planning theory. They describe spatial planning as dealing with inherent uncertainty, complexity and inevitable normativity. This contribution picks up the concept of wicked problems, reflects on it from a planning-theoretical perspective, and proposes the use of Cultural Theory's concept of clumsy solutions as a response to wicked planning problems. In discussing public participation processes in spatial planning, it is then shown what clumsy solutions mean for spatial planning. The four rationalities of Cultural Theory are then used to explain why public participation in planning can become wicked, and how these rationalities provide a response that copes with this wickedness.
Letter to the Editor : Standardizing the nomenclature for clonal lineages of the sudden oak death pathogen, Phytophthora ramorum
Grünwald, N.J. ; Goss, E.M. ; Ivors, K. ; Garbelotto, M. ; Martin, F.N. ; Prospero, S. ; Hansen, E. ; Bonants, P.J.M. ; Hamelin, R.C. ; Chastagner, M. ; Werres, S. ; Rizzo, D.M. ; Abad, G. ; Beales, P. ; Bilodeau, G.J. ; Blomquist, C.L. ; Brasier, C. ; Brière, S.C. ; Chandelier, A. ; Davidson, J.M. ; Denman, S. ; Elliott, M. ; Frankel, S.J. ; Goheen, E.M. ; Gruyter, H. de; Heungens, K. ; James, D. ; Kanaskie, A. ; McWilliams, M.G. ; Man in't Veld, W. ; Moralejo, E. ; Osterbauer, N.K. ; Palm, M.E. ; Parke, J.L. ; Perez Sierra, A.M. ; Shamoun, S.F. ; Shishkoff, N. ; Tooley, P.W. ; Vettraino, A.M. ; Webber, J. ; Widmer, T.L. - \ 2009
Phytopathology 99 (2009)7. - ISSN 0031-949X - p. 792 - 795.
in-vitro - north-american - european populations - genotypic diversity - dna polymorphisms - central mexico - toluca valley - united-states - infestans - california
Phytophthora ramorum, the causal agent of sudden oak death and ramorum blight, is known to exist as three distinct clonal lineages which can only be distinguished by performing molecular marker-based analyses. However, in the recent literature there exists no consensus on naming of these lineages. Here we propose a system for naming clonal lineages of P. ramorum based on a consensus established by the P. ramorum research community. Clonal lineages are named with a two letter identifier for the continent on which they were first found (e.g., NA = North America; EU = Europe) followed by a number indicating order of appearance. Clonal lineages known to date are designated NA1 (mating type: A2; distribution: North America; environment: forest and nurseries), NA2 (A2; North America; nurseries), and EU1 (predominantly A1, rarely A2; Europe and North America; nurseries and gardens). It is expected that novel lineages or new variants within the existing three clonal lineages could in time emerge.
|Tree doctor; diagnostic des maladies sur arbres forestiers ou d 'ornement / diagnosis of diseases of forest and ornamental trees / diagnosi delle principali avversita degli alberi forestali e da ornamento / zelf herkennen van ziekten en plagen van bomen (cd-rom)
Giry, C. ; Tourret, V. ; Descombes, P. ; Rose, D. ; Webber, J. ; Beffa, A.M. Della; Ferrara, A.M. ; Tagliaferro, E. ; Viotto, E. ; Moraal, L.G. ; Kopinga, H. ; Siepel, H. ; Maaskamp, F.I.M. ; Borst, R. ; Szabo, P. ; Bourgery, C. ; Aversenq, P. ; Nageleisen, L.M. ; Chauvel, G. ; Dodet, G. ; Dugois, M. ; Grange, C. ; Masson, B. ; Monnet, S. - \ 2007
Wageningen : Alterra [etc.]