| human | Q5 |
| P2456 | DBLP author ID | 31/3800-7 |
| P227 | GND ID | 13169720X |
| P244 | Library of Congress authority ID | nb2009029188 |
| P496 | ORCID iD | 0000-0002-9491-3550 |
| P3829 | Publons author ID | 1273299 |
| P1053 | ResearcherID | E-4812-2016 |
| P1153 | Scopus author ID | 56550089500 |
| P214 | VIAF ID | 1152283 |
| P10832 | WorldCat Entities ID | E39PBJxd6yXqjxftwPrC3JKDbd |
| P108 | employer | Potsdam Institute for Climate Impact Research | Q251061 |
| P734 | family name | Müller | Q8157228 |
| Müller | Q8157228 | ||
| Müller | Q8157228 | ||
| P735 | given name | Christoph | Q17689481 |
| Christoph | Q17689481 | ||
| P106 | occupation | researcher | Q1650915 |
| P21 | sex or gender | male | Q6581097 |
| Q111110261 | A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
| Q62928771 | A multi-model analysis of teleconnected crop yield variability in a range of cropping systems |
| Q57197379 | A network-based approach for semi-quantitative knowledge mining and its application to yield variability |
| Q57033498 | A new climate dataset for systematic assessments of climate change impacts as a function of global warming |
| Q57146962 | A statistical analysis of three ensembles of crop model responses to temperature and CO 2 concentration |
| Q57197410 | Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa |
| Q30606945 | African lessons on climate change risks for agriculture |
| Q111094461 | Agricultural breadbaskets shift poleward given adaptive farmer behavior under climate change |
| Q57197386 | Agricultural trade and tropical deforestation: interactions and related policy options |
| Q57197400 | Agriculture and climate change in global scenarios: why don't the models agree |
| Q57197364 | An AgMIP framework for improved agricultural representation in integrated assessment models |
| Q57197426 | Assessing 20th century climate-vegetation feedbacks of land-use change and natural vegetation dynamics in a fully coupled vegetation-climate model |
| Q30717120 | Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison |
| Q57197413 | Attributing the impacts of land-cover changes in temperate regions on surface temperature and heat fluxes to specific causes: Results from the first LUCID set of simulations |
| Q57129899 | Can bioenergy cropping compensate high carbon emissions from large-scale deforestation of high latitudes? |
| Q57197360 | Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change |
| Q28590151 | Climate analogues suggest limited potential for intensification of production on current croplands under climate change |
| Q30717102 | Climate change effects on agriculture: economic responses to biophysical shocks |
| Q125251091 | Climate change impacts on European arable crop yields: Sensitivity to assumptions about rotations and residue management |
| Q57197387 | Climate change impacts on agriculture in 2050 under a range of plausible socioeconomic and emissions scenarios |
| Q30395899 | Climate change risks for African agriculture |
| Q57197414 | Climate-driven simulation of global crop sowing dates |
| Q57033681 | Comparative impact of climatic and nonclimatic factors on global terrestrial carbon and water cycles |
| Q57197352 | Comparing impacts of climate change and mitigation on global agriculture by 2050 |
| Q37598486 | Consistent negative response of US crops to high temperatures in observations and crop models |
| Q28657977 | Constraints and potentials of future irrigation water availability on agricultural production under climate change |
| Q52334017 | Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments |
| Q57197373 | Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles |
| Q57146927 | Crop productivity changes in 1.5 °C and 2 °C worlds under climate sensitivity uncertainty |
| Q57197388 | Crop rotation modelling—A European model intercomparison |
| Q57197375 | Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins |
| Q57197415 | Determining Robust Impacts of Land-Use-Induced Land Cover Changes on Surface Climate over North America and Eurasia: Results from the First Set of LUCID Experiments |
| Q63951464 | Dissecting the nonlinear response of maize yield to high temperature stress with model‐data integration |
| Q57471955 | Diverging importance of drought stress for maize and winter wheat in Europe |
| Q57033432 | Drivers and patterns of land biosphere carbon balance reversal |
| Q57033635 | Effects of changes in CO2, climate, and land use on the carbon balance of the land biosphere during the 21st century |
| Q57197389 | Energy, land-use and greenhouse gas emissions trajectories under a green growth paradigm |
| Q57197108 | Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets |
| Q57197215 | Exploring global irrigation patterns: A multilevel modelling approach |
| Q125405070 | Extreme rainfall reduces one-twelfth of China’s rice yield over the last two decades |
| Q49830421 | Farming with crops and rocks to address global climate, food and soil security |
| Q57197401 | Feeding 10 billion people under climate change: How large is the production gap of current agricultural systems? |
| Q57197402 | Fertilizing hidden hunger |
| Q57197403 | Forecasting technological change in agriculture—An endogenous implementation in a global land use model |
| Q57197390 | Fossil-fueled development (SSP5): An energy and resource intensive scenario for the 21st century |
| Q57197365 | Freshwater resources under success and failure of the Paris climate agreement |
| Q62928770 | Freshwater resources under success and failure of the Paris climate agreement |
| Q114634254 | Future climate change significantly alters interannual wheat yield variability over half of harvested areas |
| Q62928777 | Generating a global gridded tillage dataset |
| Q112603394 | Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation |
| Q28741574 | Global bioenergy potentials from agricultural land in 2050: Sensitivity to climate change, diets and yields |
| Q111110221 | Global cotton production under climate change – Implications for yield and water consumption |
| Q57033624 | Global food demand, productivity growth, and the scarcity of land and water resources: a spatially explicit mathematical programming approach |
| Q57197376 | Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications |
| Q128965554 | Global irrigation contribution to wheat and maize yield |
| Q55445793 | Global patterns of crop yield stability under additional nutrient and water inputs. |
| Q57197362 | Greenhouse gas emission curves for advanced biofuel supply chains |
| Q57197419 | Harvesting from uncertainties |
| Q57197423 | Harvesting the sun: New estimations of the maximum population of planet Earth |
| Q30814433 | Hotspots of climate change impacts in sub-Saharan Africa and implications for adaptation and development |
| Q57197382 | How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield? |
| Q30727193 | How do various maize crop models vary in their responses to climate change factors? |
| Q57160809 | Implementing the Nitrogen cycle into the dynamic global vegetation, hydrology and crop growth model LPJmL (version 5) |
| Q57160757 | Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0) |
| Q57146978 | Implications of climate mitigation for future agricultural production |
| Q47107166 | Improving the use of crop models for risk assessment and climate change adaptation |
| Q112814700 | Insights on Nitrogen and Phosphorus Co‐Limitation in Global Croplands From Theoretical and Modeling Fertilization Experiments |
| Q111221965 | Insights on nitrogen and phosphorus co-limitation in global croplands from theoretical and modelling fertilization experiments |
| Q57197416 | Integrating the complexity of global change pressures on land and water |
| Q57197405 | Investigating afforestation and bioenergy CCS as climate change mitigation strategies |
| Q26745524 | Key knowledge and data gaps in modelling the influence of CO2 concentration on the terrestrial carbon sink |
| Q57197353 | LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description |
| Q57197354 | LPJmL4 – a dynamic global vegetation model with managed land – Part 2: Model evaluation |
| Q57197434 | Land in sight?Achievements, deficits and potentials of continental to global scale land-use modeling |
| Q30943642 | Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation? |
| Q57197406 | Land-use protection for climate change mitigation |
| Q112604231 | Large potential for crop production adaptation depends on available future varieties |
| Q51145537 | Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts. |
| Q57197355 | Large-scale bioenergy production: how to resolve sustainability trade-offs? |
| Q54388306 | Linked sustainability challenges and trade-offs among fisheries, aquaculture and agriculture. |
| Q57197392 | Livestock in a changing climate: production system transitions as an adaptation strategy for agriculture |
| Q57197367 | Livestock production and the water challenge of future food supply: Implications of agricultural management and dietary choices |
| Q117423938 | Management-induced changes in soil organic carbon on global croplands |
| Q57197417 | Measuring agricultural land-use intensity – A global analysis using a model-assisted approach |
| Q57197407 | Meeting the radiative forcing targets of the representative concentration pathways in a world with agricultural climate impacts |
| Q31149424 | Mitigation Strategies for Greenhouse Gas Emissions from Agriculture and Land-Use Change: Consequences for Food Prices |
| Q57197358 | Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6 |
| Q62928774 | Modelling cropping periods of grain crops at the global scale |
| Q63491819 | Modelling forest plantations for carbon uptake with the LPJmL dynamic global vegetation model |
| Q57197383 | Multi-wheat-model ensemble responses to interannual climate variability |
| Q30862883 | Multimodel ensembles of wheat growth: many models are better than one. |
| Q30717084 | Multisectoral climate impact hotspots in a warming world |
| Q112593441 | Narrowing uncertainties in the effects of elevated CO2 on crops |
| Q112811339 | Occurrence of crop pests and diseases has largely increased in China since 1970 |
| Q59782111 | Options to model the effects of tillage on N2O emissions at the global scale |
| Q36227858 | Plausible rice yield losses under future climate warming |
| Q114164417 | Potential impacts of climate change on agriculture and fisheries production in 72 tropical coastal communities |
| Q125405435 | Projected landscape-scale repercussions of global action for climate and biodiversity protection |
| Q112605665 | Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales |
| Q57197408 | Projecting future crop productivity for global economic modeling |
| Q57202255 | Publisher Correction: Farming with crops and rocks to address global climate, food and soil security |
| Q57197436 | Quantifying geomorphological heterogeneity to assess species diversity of set-aside arable land |
| Q57197385 | Rapid aggregation of global gridded crop model outputs to facilitate cross-disciplinary analysis of climate change impacts in agriculture |
| Q38912819 | Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution |
| Q57146945 | Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity |
| Q57161299 | Rising temperatures reduce global wheat production |
| Q57197409 | Robust relationship between yields and nitrogen inputs indicates three ways to reduce nitrogen pollution |
| Q57033672 | Robustness of terrestrial carbon and water cycle simulations against variations in spatial resolution |
| Q126191615 | Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a) |
| Q57033600 | Scenarios of global bioenergy production: The trade-offs between agricultural expansion, intensification and trade |
| Q57197411 | Separate and combined effects of temperature and precipitation change on maize yields in sub-Saharan Africa for mid- to late-21st century |
| Q57161257 | Similar estimates of temperature impacts on global wheat yield by three independent methods |
| Q59782117 | Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage) |
| Q57197393 | Simulation of the phenological development of wheat and maize at the global scale |
| Q114107130 | Soil organic carbon dynamics from agricultural management practices under climate change |
| Q114163994 | Soil quality both increases crop production and improves resilience to climate change |
| Q57197112 | Sources of uncertainty in hydrological climate impact assessment: a cross-scale study |
| Q57197395 | Spatial and temporal uncertainty of crop yield aggregations |
| Q62927447 | State-of-the-art global models underestimate impacts from climate extremes |
| Q57197397 | Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces |
| Q38642028 | Temperature increase reduces global yields of major crops in four independent estimates |
| Q111110248 | The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0) |
| Q63951463 | The Global Gridded Crop Model Intercomparison phase 1 simulation dataset |
| Q57146988 | The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0) |
| Q57197371 | The International Heat Stress Genotype Experiment for modeling wheat response to heat: field experiments and AgMIP-Wheat multi-model simulations |
| Q57197418 | The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use |
| Q57197424 | The effect of temporal aggregation of weather input data on crop growth models’ results |
| Q31125465 | The impact of high-end climate change on agricultural welfare |
| Q57197398 | The impact of land-use change on the sensitivity of terrestrial productivity to precipitation variability: a modelling approach |
| Q117423150 | The role of cover crops for cropland soil carbon, nitrogen leaching, and agricultural yields – a global simulation study with LPJmL (V. 5.0-tillage-cc) |
| Q39573048 | The uncertainty of crop yield projections is reduced by improved temperature response functions. |
| Q57197218 | The yield gap of global grain production: A spatial analysis |
| Q57197428 | Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study |
| Q57197377 | Uncertainties in global crop model frameworks: effects of cultivar distribution, crop management and soil handling on crop yield estimates |
| Q57197412 | Uncertainty in simulating wheat yields under climate change |
| Q57197380 | Uncertainty of wheat water use: Simulated patterns and sensitivity to temperature and CO 2 |
| Q57141515 | Understanding the weather signal in national crop-yield variability |
| Q57197427 | Virtual water content of temperate cereals and maize: Present and potential future patterns |
| Q112814714 | Water Use in Global Livestock Production—Opportunities and Constraints for Increasing Water Productivity |
| Q57197361 | Web-based access, aggregation, and visualization of future climate projections with emphasis on agricultural assessments |
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