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- ItemClassifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change(Amsterdam [u.a.] : Elsevier, 2017) Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; Asseng, Senthold; Baranowski, Piotr; Basso, Bruno; Bodin, Per; Buis, Samuel; Cammarano, Davide; Deligios, Paola; Destain, Marie-France; Dumont, Benjamin; Ewert, Frank; Ferrise, Roberto; François, Louis; Gaiser, Thomas; Hlavinka, Petr; Jacquemin, Ingrid; Kersebaum, Kurt Christian; Kollas, Chris; Krzyszczak, Jaromir; Lorite, Ignacio J.; Minet, Julien; Minguez, M. Ines; Montesino, Manuel; Moriondo, Marco; Müller, Christoph; Nendel, Claas; Öztürk, Isik; Perego, Alessia; Rodríguez, Alfredo; Ruane, Alex C.; Ruget, Françoise; Sanna, Mattia; Semenov, Mikhail A.; Slawinski, Cezary; Stratonovitch, Pierre; Supit, Iwan; Waha, Katharina; Wang, Enli; Wu, Lianhai; Zhao, Zhigan; Rötter, Reimund P.Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
- ItemLivelihood and climate trade-offs in Kenyan peri-urban vegetable production(Amsterdam [u.a.] : Elsevier, 2017) Kurgat, Barnabas K.; Stöber, Silke; Mwonga, Samuel; Lotze-Campen, Hermann; Rosenstock, Todd S.Trade-offs between livelihood and environmental outcomes due to agricultural intensification in sub-Saharan Africa are uncertain. The present study measured yield, economic performance and nitrous oxide (N2O) emissions in African indigenous vegetable (AIV) production to investigate the optimal nutrient management strategies. In order to achieve this, an on-farm experiment with four treatments – (1) 40 kg N/ha diammonium phosphate (DAP), (2) 10 t/ha cattle manure, (3) 20 kg N/ha DAP and 5 t/ha cattle manure and (4) a no-N input control – was performed for two seasons. Yields and N2O emissions were directly measured with subsampling and static chambers/gas chromatography, respectively. Economic outcomes were estimated from semi-structured interviews (N = 12). Trade-offs were quantified by calculating N2O emissions intensity (N2OI) and N2O emissions economic intensity (N2OEI). The results indicate that, DAP alone resulted at least 14% greater yields, gross margin and returns to labour in absolute terms but had the highest emissions (p = 0.003). Productivity-climate trade-offs, expressed as N2OI, were statistically similar for DAP and mixed treatments. However, N2OEI was minimized under mixed management (p = 0.0004) while maintaining productivity and gross margins. We therefore conclude that soil fertility management strategies that mix inorganic and organic source present a pathway to sustainable intensification in AIV production. Future studies of GHG emissions in crop production need to consider not only productivity but economic performance when considering trade-offs.
- ItemPerformance of seasonal forecasts for the flowering and veraison of two major Portuguese grapevine varieties(Amsterdam [u.a.] : Elsevier, 2023) Yang, Chenyao; Ceglar, Andrej; Menz, Christoph; Martins, Joana; Fraga, Helder; Santos, João A.Seasonal phenology forecasts are becoming increasingly demanded by winegrowers and viticulturists. Forecast performance needs to be investigated over space and time before practical applications. We assess seasonal forecast performance (skill, probability and accuracy) in predicting flowering and veraison stages of two representative varieties in Portugal over 1993–2017. The state-of-the-art forecast system ECMWF-SEAS5 provides 7-month seasonal forecasts and is coupled with a locally adapted phenology model. Overall, findings illustrate the dependence of forecast performance on initialization timings, regions and predicting subjects (stages and varieties). Forecast performance improves by delaying the initialization timing and only forecasts initialized on April 1st show better skills than climatology on predicting phenology terciles (early/normal/late). The considerable bias of daily values of seasonal climate predictions can represent the main barrier to accurate forecasts. Better prediction performance is consistently found in Central-Southern regions compared to Northern regions, attributing to an earlier phenology occurrence with a shorter forecast length. Comparable predictive skills between flowering and veraison for both varieties imply better predictability in summer. Consequently, promising seasonal phenology predictions are foreseen in Central-Southern wine regions using forecasts initialized on April 1st with approximately 1–2/3–4 months lead time for flowering/veraison: potential prediction errors are ∼2 weeks, along with an overall moderate forecast skill on categorical events. However, considerable inter-annual variability of forecast performance over the same classified phenology years reflects the substantial influence of climate variability. This may represent the main challenge for reliable forecasts in Mediterranean regions. Recommendations are suggested for methodological innovations and practical applications towards reliable regional phenology forecasts.
- ItemChapter scientists in the IPCC AR5-experience and lessons learned(Amsterdam [u.a.] : Elsevier, 2015) Schulte-Uebbing, Lena; Hansen, Gerrit; Hernández, Ariel Macaspac; Winter, MartenIPCC Assessment Reports provide timely and accurate information on anthropogenic climate change to policy makers and the public. The reports are written by hundreds of scientists in a voluntary, collaborative effort. Growing amounts of literature and complex procedural and administrative requirements, however, make this effort a substantial management challenge next to a scientific one. During the 5th Assessment Cycle, IPCC Working Groups II and III initiated a program that recruited volunteer scientific assistants who provided technical and logistical support to author teams. In this paper we describe and analyze strengths and weaknesses of this ‘Chapter Scientist program’, based on an extensive survey among Chapter Scientists (CS) and interviews with other stakeholders. We conclude that the program was a useful innovation that that enabled authors to focus more on their core scientific tasks and that contributed to improving the quality of the assessment. We highly recommend similar programs for future scientific assessments. Key criteria for success that we identified are (a) involvement of early-career scientists as CS, (b) close integration of CS in the assessment process, (c) recruitment of CS through an open call to achieve transparency, and (d) provision of funds for such a program to support travel costs and compensation of CS.
- ItemGlobal and country-level data of the biodiversity footprints of 175 crops and pasture(Amsterdam [u.a.] : Elsevier, 2021) Beyer, Robert; Manica, AndreaThe destruction of natural habitat for cropland and pasture represents a major threat to global biodiversity. Despite widespread societal concern about biodiversity loss associated with food production, consumer access to quantitative estimates of the impact of crop production on the world's species has been very limited compared to assessments of other environmental variables such as greenhouse gas emissions or water use. Here, we present a consistent dataset of the biodiversity footprints of pasture and 175 crops at the global and national level. The data were generated by combining maps of the global distribution of agricultural areas in the year 2000 with spatially explicit estimates of the biodiversity loss associated with the conversion of natural habitat to farmland. Estimates were derived for three common alternative measures of biodiversity - species richness, threatened species richness, and range rarity - of the world's mammals, birds, and amphibians. Our dataset provides important quantitative information for food consumers and policy makers, allowing them to take evidence-based decisions to reduce the biodiversity footprint of global food production.
- ItemOpening up knowledge systems for better responses to global environmental change(Amsterdam [u.a.] : Elsevier, 2013) Cornell, S.; Berkhout, F.; Tuinstra, W.; Tàbara, J.D.; Jäger, J.; Chabay, I.; de Wit, B.; Langlais, R.; Mills, D.; Moll, P.; Otto, I.M.; Petersen, A.; Pohl, C.; van Kerkhoff, L.Linking knowledge with action for effective societal responses to persistent problems of unsustainability requires transformed, more open knowledge systems. Drawing on a broad range of academic and practitioner experience, we outline a vision for the coordination and organization of knowledge systems that are better suited to the complex challenges of sustainability than the ones currently in place. This transformation includes inter alia: societal agenda setting, collective problem framing, a plurality of perspectives, integrative research processes, new norms for handling dissent and controversy, better treatment of uncertainty and of diversity of values, extended peer review, broader and more transparent metrics for evaluation, effective dialog processes, and stakeholder participation. We set out institutional and individual roadmaps for achieving this vision, calling for well-designed, properly resourced, longitudinal, international learning programs.
- ItemCorrecting a fundamental error in greenhouse gas accounting related to bioenergy(Amsterdam [u.a.] : Elsevier, 2012) Haberl, H.; Sprinz, D.; Bonazountas, M.; Cocco, P.; Desaubies, Y.; Henze, M.; Hertel, O.; Johnson, R.K.; Kastrup, U.; Laconte, P.; Lange, E.; Novak, P.; Paavola, J.; Reenberg, A.; van den Hove, S.; Vermeire, T.; Wadhams, P.; Searchinger, T.Many international policies encourage a switch from fossil fuels to bioenergy based on the premise that its use would not result in carbon accumulation in the atmosphere. Frequently cited bioenergy goals would at least double the present global human use of plant material, the production of which already requires the dedication of roughly 75% of vegetated lands and more than 70% of water withdrawals. However, burning biomass for energy provision increases the amount of carbon in the air just like burning coal, oil or gas if harvesting the biomass decreases the amount of carbon stored in plants and soils, or reduces carbon sequestration. Neglecting this fact results in an accounting error that could be corrected by considering that only the use of 'additional biomass' - biomass from additional plant growth or biomass that would decompose rapidly if not used for bioenergy - can reduce carbon emissions. Failure to correct this accounting flaw will likely have substantial adverse consequences. The article presents recommendations for correcting greenhouse gas accounts related to bioenergy.
- ItemBio-IGCC with CCS as a long-term mitigation option in a coupled energy-system and land-use model(Amsterdam [u.a.] : Elsevier, 2011) Klein, D.; Bauer, N.; Bodirsky, B.; Dietrich, J.P.; Popp, A.This study analyses the impact of techno-economic performance of the BIGCC process and the effect of different biomass feedstocks on the technology's long term deployment in climate change mitigation scenarios. As the BIGCC technology demands high amounts of biomass raw material it also affects the land-use sector and is dependent on conditions and constraints on the land-use side. To represent the interaction of biomass demand and supply side the global energy-economy-climate model ReMIND is linked to the global land-use model MAgPIE. The link integrates biomass demand and price as well as emission prices and land-use emissions. Results indicate that BIGCC with CCS could serve as an important mitigation option and that it could even be the main bioenergy conversion technology sharing 33% of overall mitigation in 2100. The contribution of BIGCC technology to long-term climate change mitigation is much higher if grass is used as fuel instead of wood, provided that the grass-based process is highly efficient. The capture rate has to significantly exceed 60 % otherwise the technology is not applied. The overall primary energy consumption of biomass reacts much more sensitive to price changes of the biomass than to technoeconomic performance of the BIGCC process. As biomass is mainly used with CCS technologies high amounts of carbon are captured ranging from 130 GtC to 240 GtC (cumulated from 2005-2100) in different scenarios.
- ItemHow modelers construct energy costs: Discursive elements in Energy System and Integrated Assessment Models(Amsterdam [u.a.] : Elsevier, 2019) Ellenbeck, Saskia; Lilliestam, JohanEnergy system and integrated assessment models (IAMs) are widely used techniques for knowledge production to assess costs of future energy pathways and economic effects of energy/climate policies. With their increased use for policy assessment and increasing dominance in energy policy science, such models attract increasing criticism. In the last years, such models – especially the highly complex IAMs, have been accused of being arbitrary. We challenge this view and argue that the models and their assumptions are not arbitrary, but they are normative and reflect the modelers’ understanding of the functioning of the society, the environment-societal relations and respective appropriate scientific tools and theories – in short: models are shaped by discursive structures, reproducing and reinforcing particular societal discourses. We identify 9 distinct paths, all relating to crucial model decisions, via which discourses enter models: for each of these decisions, there are multiple “correct” answers, in the sense that they can be justified within a particular discourse. We conclude that decisions of modelers about the structure and about assumptions in energy modeling are not arbitrary but contingent to the discursive context the modeler is related to. This has two implications. First, modelers and consumers of model output must reflect on what a model and its assumptions represent, and not only whether are they correct. Second, models hardly need to add more (mathematical) complexity, but rather be reduced and simplified so that they can continue to fulfill their main function as formalized and powerful instruments for thought experiments about future energy pathways.
- ItemMulti-method evidence for when and how climate-related disasters contribute to armed conflict risk(Amsterdam [u.a.] : Elsevier, 2020) Ide, Tobias; Brzoska, Michael; Donges, Jonathan F.; Schleussner, Carl-FriedrichClimate-related disasters are among the most societally disruptive impacts of anthropogenic climate change. Their potential impact on the risk of armed conflict is heavily debated in the context of the security implications of climate change. Yet, evidence for such climate-conflict-disaster links remains limited and contested. One reason for this is that existing studies do not triangulate insights from different methods and pay little attention to relevant context factors and especially causal pathways. By combining statistical approaches with systematic evidence from QCA and qualitative case studies in an innovative multi-method research design, we show that climate-related disasters increase the risk of armed conflict onset. This link is highly context-dependent and we find that countries with large populations, political exclusion of ethnic groups, and a low level of human development are particularly vulnerable. For such countries, almost one third of all conflict onsets over the 1980-2016 period have been preceded by a disaster within 7 days. The robustness of the effect is reduced for longer time spans. Case study evidence points to improved opportunity structures for armed groups rather than aggravated grievances as the main mechanism connecting disasters and conflict onset. © 2020 The Authors