TY  - JOUR
A1  - Pohanková, Eva
A1  - Hlavinka, Petr
A1  - Kersebaum, Kurt-Christian
A1  - Rodríguez, Alfredo
A1  - Balek, Jan
A1  - Bednařík, Martin
A1  - Dubrovský, Martin
A1  - Gobin, Anne
A1  - Hoogenboom, Gerrit
A1  - Moriondo, Marco
A1  - Nendel, Claas
A1  - Olesen, Jørgen E. E.
A1  - Rötter, Reimund Paul
A1  - Ruiz-Ramos, Margarita
A1  - Shelia, Vakhtang
A1  - Stella, Tommaso
A1  - Hoffmann, Munir Paul
A1  - Takáč, Jozef
A1  - Eitzinger, Josef
A1  - Dibari, Camilla
A1  - Ferrise, Roberto
A1  - Bláhová, Monika
A1  - Trnka, Miroslav
T1  - Expected effects of climate change on the production and water use of crop rotation management reproduced by crop model ensemble for Czech Republic sites
JF  - European journal of agronomy
N2  - Crop rotation, fertilization and residue management affect the water balance and crop production and can lead to different sensitivities to climate change. To assess the impacts of climate change on crop rotations (CRs), the crop model ensemble (APSIM,AQUACROP, CROPSYST, DAISY, DSSAT, HERMES, MONICA) was used. The yields and water balance of two CRs with the same set of crops (winter wheat, silage maize, spring barley and winter rape) in a continuous transient run from 1961 to 2080 were simulated. CR1 was without cover crops and without manure application. Straw after the harvest was exported from the fields. CR2 included cover crops, manure application and crop residue retention left on field. Simulations were performed using two soil types (Chernozem, Cambisol) within three sites in the Czech Republic, which represent temperature and precipitation gradients for crops in Central Europe. For the description of future climatic conditions, seven climate scenarios were used. Six of them had increasing CO & nbsp;concentrations according RCP 8.5, one had no CO2 increase in the future. The output of an ensemble expected higher productivity by 0.82 t/ha/year and 2.04 t/ha/year for yields and aboveground biomass in the future (2051-2080). However, if the direct effect of a CO2 increase is not considered, the average yields for lowlands will be lower. Compared to CR1, CR2 showed higher average yields of 1.26 t/ha/year for current climatic conditions and 1.41 t/ha/year for future climatic conditions. For the majority of climate change scenarios, the crop model ensemble agrees on the projected yield increase in C3 crops in the future for CR2 but not for CR1. Higher agreement for future yield increases was found for Chernozem, while for Cambisol, lower yields under dry climate scenarios are expected. For silage maize, changes in simulated yields depend on locality. If the same hybrid will be used in the future, then yield reductions should be expected within lower altitudes. The results indicate the potential for higher biomass production from cover crops, but CR2 is associated with almost 120 mm higher evapotranspiration compared to that of CR1 over a 5-year cycle for lowland stations in the future, which in the case of the rainfed agriculture could affect the long-term soil water balance. This could affect groundwater replenishment, especially for locations with fine textured soils, although the findings of this study highlight the potential for the soil water-holding capacity to buffer against the adverse weather conditions.
KW  - Yields
KW  - Evapotranspiration
KW  - Winter wheat
KW  - Silage maize
KW  - Spring barley
KW  - Winter oilseed rape
Y1  - 2022
U6  - https://doi.org/10.1016/j.eja.2021.126446
SN  - 1161-0301
SN  - 1873-7331
VL  - 134
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Kothari, Kritika
A1  - Battisti, Rafael
A1  - Boote, Kenneth J.
A1  - Archontoulis, Sotirios
A1  - Confalone, Adriana
A1  - Constantin, Julie
A1  - Cuadra, Santiago
A1  - Debaeke, Philippe
A1  - Faye, Babacar
A1  - Grant, Brian
A1  - Hoogenboom, Gerrit
A1  - Jing, Qi
A1  - van der Laan, Michael
A1  - Macena da Silva, Fernando Antonio
A1  - Marin, Fabio R.
A1  - Nehbandani, Alireza
A1  - Nendel, Claas
A1  - Purcell, Larry C.
A1  - Qian, Budong
A1  - Ruane, Alex C.
A1  - Schoving, Celine
A1  - Silva, Evandro H. F. M.
A1  - Smith, Ward
A1  - Soltani, Afshin
A1  - Srivastava, Amit
A1  - Vieira, Nilson A.
A1  - Slone, Stacey
A1  - Salmeron, Montserrat
T1  - Are soybean models ready for climate change food impact assessments?
JF  - European journal of agronomy : the official journal of the European Society for Agronomy
N2  - An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 degrees C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 degrees C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models.
KW  - Agricultural Model Inter-comparison and Improvement Project (AgMIP);
KW  - Model ensemble
KW  - Model calibration
KW  - Temperature
KW  - Atmospheric CO2
KW  - concentration
KW  - Legume model
Y1  - 2022
U6  - https://doi.org/10.1016/j.eja.2022.126482
SN  - 1161-0301
SN  - 1873-7331
VL  - 135
PB  - Elsevier
CY  - Amsterdam
ER  -