Abstract: This special issue includes a sub-set of papers developed in the context of the three-years (2013-16) research project “IC-FAR – Linking long term observatories with crop system modelling for a better understanding of climate change impact and adaptation strategies for Italian cropping systems” (www.icfar.it), funded by the Italian Ministry of Education, University and Research. IC-FAR collects the legacy of some three-four generations of researchers, members of the Italian Society of Agronomy, that from the 1960ies onward established long term agro-ecosystem experiments (LTAE) in various Italian locations, to address a wide range of agronomy research questions. A lot of the results from these LTAE were not yet published or were published as grey literature or in Italian and almost always as a single-site, single-experiment outcome.

Abstract: Maize (Zea mays L.) is the most prominent crop in the Northeast Farming Region of China (NFR), and drought has been the largest limitation for maize production in this area during recent decades. The question of how to adapt maize production to drought has received great attention from policy makers, researchers and farmers. In order to evaluate the effects of adaptation strategies against drought and examine the influences of policy supports and farmer households’ characteristics on adopting decisions, a large scale household survey was conducted in five representative maize production counties across NFR. Our survey results indicated that using variety diversification, drought resistant varieties and dibbling irrigation are the three major adaptation strategies against drought in spring, and farmers also adopted changes in sowing time, conservation tillage and mulching to cope with drought in spring. About 20% and 18% of households enhanced irrigation against drought in summer and autumn, respectively. Deep loosening tillage and organic fertilizer are also options for farmers to resist drought in summer. Maize yield was highly dependent on soil qualities, with yields on land of high soil quality approximately 1050 kg/ha and 2400 kg/ha higher than for normal and poor soil conditions, respectively. Using variety diversification and drought resistant varieties can respectively increase maize yield by approximately 150 and 220 kg/ha under drought. Conservation tillage increased maize yield by 438–459 kg/ha in drought years. Irrigation improved maize yield by 419–435 kg/ha and 444–463 kg/ha against drought in summer and autumn, respectively. Offering information service, financial and technical support can greatly increase the use of adaptation strategies for farmers to cope with drought. However, only 46% of households received information service, 43% of households received financial support, and 26% of households received technical support against drought from the local government. The maize acreage and the irrigation access are the major factors that influenced farmers’ decisions to apply adaptation strategies to cope with drought in each season, but only 25% of households have access to irrigation. This indicates the need for enhanced public support for farmers to better cope with drought in maize production, particularly through improving access to irrigation.

Abstract: • ICFAR-DB organises and stores data from 16 Italian long term agronomic experiments. • ICFAR-DB fulfils interoperability using system dynamics ontology and AgMIP nomenclature. • ICFAR information management system moves closer data to model and vice versa. The IC-FAR national project (Linking long term observatories with crop system modelling for better understanding of climate change impact, and adaptation strategies for Italian cropping systems) initiated in 2013 with the primary aim of implementing data from 16 long term Italian agronomic experiments in a common, interoperable structure. The building of a common database (DB) structure demands a harmonization process aimed at standardising concepts, language and data in order to make them clear, and has to produce a well-documented and easily available tool for the whole scientific community. The Agricultural Model Intercomparison and Improvement Project (AgMIP) has made a great effort in this sense, improving the vocabulary developed by the International Consortium for Agricultural Systems Applications (ICASA) and defining harmonization procedures. Nowadays, these ones have also to be addressed to facilitate the extraction of input files for crop model simulations. Substantially, two alternative directions can be pursued: adapting data to models, building a standard storage structure and using translators that convert DB information to model input files; or adapting models to data, using the same storage structure for feeding modelling solutions constituted by combining model components, re-implemented in the same model platform. The ICFAR information management system simplifies data entry, improves model input extraction (implementing System Dynamics ontology), and satisfies both the paradigms. This has required the development of different software tools: ICFAR-DB for data entry and storage; a model input extractor for feeding the crop models (MoLInEx); SEMoLa platform for building modelling solutions and performing via scripts the model intercomparison. The use of the standard AgMIP/ICASA nomenclature in the ICFAR-DB and the opportunity to create files with MoLInex for feeding AgMIP model translators allow full system interoperability.