Search Results
Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change
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.
Chapter scientists in the IPCC AR5-experience and lessons learned
IPCC 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.
The social cost of carbon and inequality: When local redistribution shapes global carbon prices
The social cost of carbon is a central metric for optimal carbon prices. Previous literature shows that inequality significantly influences the social cost of carbon, but mostly omits heterogeneity below the national level. We present an optimal taxation model of the social cost of carbon that accounts for inequality between and within countries. We find that climate and distributional policy can generally not be separated. If only one country does not compensate low-income households for disproportionate damages, the social cost of carbon tends to increase globally. Optimal carbon prices remain roughly unchanged if national redistribution leaves inequality between households unaffected by climate change and if the utility of households is approximately logarithmic in consumption.
Land-use futures in the shared socio-economic pathways
In the future, the land system will be facing new intersecting challenges. While food demand, especially for resource-intensive livestock based commodities, is expected to increase, the terrestrial system has large potentials for climate change mitigation through improved agricultural management, providing biomass for bioenergy, and conserving or even enhancing carbon stocks of ecosystems. However, uncertainties in future socio-economic land use drivers may result in very different land-use dynamics and consequences for land-based ecosystem services. This is the first study with a systematic interpretation of the Shared Socio-Economic Pathways (SSPs) in terms of possible land-use changes and their consequences for the agricultural system, food provision and prices as well as greenhouse gas emissions. Therefore, five alternative Integrated Assessment Models with distinctive land-use modules have been used for the translation of the SSP narratives into quantitative projections. The model results reflect the general storylines of the SSPs and indicate a broad range of potential land-use futures with global agricultural land of 4900 mio ha in 2005 decreasing by 743 mio ha until 2100 at the lower (SSP1) and increasing by 1080 mio ha (SSP3) at the upper end. Greenhouse gas emissions from land use and land use change, as a direct outcome of these diverse land-use dynamics, and agricultural production systems differ strongly across SSPs (e.g. cumulative land use change emissions between 2005 and 2100 range from −54 to 402 Gt CO2). The inclusion of land-based mitigation efforts, particularly those in the most ambitious mitigation scenarios, further broadens the range of potential land futures and can strongly affect greenhouse gas dynamics and food prices. In general, it can be concluded that low demand for agricultural commodities, rapid growth in agricultural productivity and globalized trade, all most pronounced in a SSP1 world, have the potential to enhance the extent of natural ecosystems, lead to lowest greenhouse gas emissions from the land system and decrease food prices over time. The SSP-based land use pathways presented in this paper aim at supporting future climate research and provide the basis for further regional integrated assessments, biodiversity research and climate impact analysis. © 2016 The Authors
Livelihood and climate trade-offs in Kenyan peri-urban vegetable production
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.
Global and country-level data of the biodiversity footprints of 175 crops and pasture
The 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.
How modelers construct energy costs: Discursive elements in Energy System and Integrated Assessment Models
Energy 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.
Performance of seasonal forecasts for the flowering and veraison of two major Portuguese grapevine varieties
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.
Climate change impacts on European arable crop yields: Sensitivity to assumptions about rotations and residue management
Most large scale studies assessing climate change impacts on crops are performed with simulations of single crops and with annual re-initialization of the initial soil conditions. This is in contrast to the reality that crops are grown in rotations, often with sizable proportion of the preceding crop residue to be left in the fields and varying soil initial conditions from year to year. In this study, the sensitivity of climate change impacts on crop yield and soil organic carbon to assumptions about annual model re-initialization, specification of crop rotations and the amount of residue retained in fields was assessed for seven main crops across Europe. Simulations were conducted for a scenario period 2040–2065 relative to a baseline from 1980 to 2005 using the SIMPLACE1 framework. Results indicated across Europe positive climate change impacts on yield for C3 crops and negative impacts for maize. The consideration of simulating rotations did not have a benefit on yield variability but on relative yield change in response to climate change which slightly increased for C3 crops and decreased for C4 crops when rotation was considered. Soil organic carbon decreased under climate change in both simulations assuming a continuous monocrop and plausible rotations by between 1% and 2% depending on the residue management strategy.
Sustainable food protein supply reconciling human and ecosystem health: A Leibniz Position
Many global health risks are related to what and how much we eat. At the same time, the production of food, especially from animal origin, contributes to environmental change at a scale that threatens boundaries of a safe operating space for humanity. Here we outline viable solutions how to reconcile healthy protein consumption and sustainable protein production which requires a solid, interdisciplinary evidence base. We review the role of proteins for human and ecosystem health, including physiological effects of dietary proteins, production potentials from agricultural and aquaculture systems, environmental impacts of protein production, and mitigation potentials of transforming current production systems. Various protein sources from plant and animal origin, including insects and fish, are discussed in the light of their health and environmental implications. Integration of available knowledge is essential to move from a dual problem description (“healthy diets versus environment”) towards approaches that frame the food challenge of reconciling human and ecosystem health in the context of planetary health. This endeavor requires a shifting focus from metrics at the level of macronutrients to whole diets and a better understanding of the full cascade of health effects caused by dietary proteins, including health risks from food-related environmental degradation. © 2020