More and more agricultural and environmental data are now available. These data are produced by numerous methods: Terrestrial sensors, remote sensing systems, simulation models, Internet of things, etc. Agricultural and environmental Information Systems (IS) and Decision Support Systems (DSS) are two complementary approaches to use these data – their joint use allows managing information and making decisions based on their analysis in numerous applications for agriculture and environment. In the second edition of this special issue, we publish the latest advances in the field of informatics applied to agriculture and environment, focusing on the information and decision system technologies. The published papers range from the formal systems modelling to their development and experiments for decision-making. Several of these contributions show the combination of theoretical and practical methods issued from multidisciplinary research works. Different applications are presented in the fields of land use and pasture modelling, analyse of climate change impacts on agriculture, GM maize crop management, biotechnology and agriculture, fishery management. The communication and the interaction with users are two key points for the IS and DSS usability. The paper “An authoring tool for decision support systems in context questions of ecological knowledge” presents a new system to query more easily information and decision systems for biotechnology and agriculture. This method is based on a natural language interface in which the interactions between the user and the DSS reference the previous questions and answers. The system provides the capability to elide certain parts of the questions. The proposal is based on ontologies created semi-automatically by information integration. The architecture has been tested with information coming from the CEREALAB database and the Web (e.g., PubMed). The paper “Inference reasoning on fishers' knowledge using Bayesian causal maps” deals with a theoretical formalism for knowledge representation. The authors show how to use a new formalism called Bayesian causal map to model shellfish dredger activities and derive a decision systems allowing scenarios testing for fisheries management. Bayesian causal maps combine the advantages of cognitive maps and Bayesian networks. The resulting method is easy to use for expressing knowledge and for eliciting uncertain information. In the paper “Bayesian calibration of the Pasture Simulation model (PaSim) to simulate European grasslands under water stress”, the authors present a framework to interpret the model performance obtained with Bayesian calibration, in taking into account the case of a complex model for grassland. This model called PaSim is defined under certain climate conditions (precipitation reduction). The authors show an application for grasslands in Europe. In many places, urban zones tend to replace rural areas and it is important to be able to estimate the evolution of this tendency. In the paper “Supporting planning activities with the assessment and the prediction of urban sprawl using spatio-temporal analysis”, the authors analyse the spatio-temporal evolution of land and soil data. The authors introduce a model to measure variations occurred in land use, determine soil consumption and assess future trends. This model is applied to an Italian region. The managing of the coexistence between GM and non-GM maize crops is an important issue for numerous stakeholders. In the paper “Design of a decision support tool for managing coexistence between genetically modified and conventional maize at farm and regional levels”, the authors develop a model that can be used to inform the decision-maker on adventitious presence of GM grains in non-GM agricultural areas. Information are also provided about the uncertainty of the assessment and about the variability of adventitious presence. The implemented Web-based decision-support tool can compute the expected adventitious presence and its probability distribution in non-GM maize fields, according to distance and date. In “An open platform to assess vulnerabilities to climate change: An application to agricultural systems”, the authors introduce a new software platform for quantitative assessments support of vulnerability to climate change in agriculture. This software tool allows processing model-based inference related to agro-ecological system vulnerability to a variety of climate scenarios. A case study is introduced in the Massif Central region in France. The platform is used to characterize climate, soils and human management and to assess the vulnerability to climate change of grassland productivity at a fine geographical scale. In conclusion, this special issue describes some applications of information/decision systems and shows how these types of systems can help to manage the future challenges in the environmental and agricultural field. The world will have to face many challenges such as agricultural adaptation to climate change, land use evolution, coexistence of various agricultural systems, environmental constraints, etc. and information/decision systems will offer technical means to address these challenges.