Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.

Appreciation for agricultural sustainability and ecosystem services (ESS) has received considerable attention from the scientific community. However, research has not yet systematically and sufficiently considered the spatial dimension of ESS trade-offs as a source of conflicts. Moreover, approaches for ESS management that address a wide range of beneficiaries and their interactions at landscape scale are lacking. Our main research question is how to motivate different beneficiaries of agricultural landscapes to cooperate in reducing supply–demand mismatches and accompanied conflicts, as well as to assess how different scenarios would impact relevant Sustainable Development Goals (SDGs). We present a novel and conceptual integrated model in which we employ a combination of three methodological tools: participatory geographic information system (PGIS), agent-based modelling (ABM) and a Bayesian belief network (BBN). The objective of our model simulation is to identify and manage site-specific spatial trade-off patterns and to provide decision support for shifting competitive behavior of individual stakeholders in satisfying their demand for ESS to a collective and cooperative scheme, while jointly striving to attain relevant targets outlined in the SDGs. Attached to this work is a short video depicting our conceptual model. We strongly suggest that tackling a complex social-ecological system necessitates a highly integrated modelling approach that fosters the transition from farm- to landscape-scale management, from individualistic to collective action, and from competitive to cooperative behavior.

Agricultural land use systems have been optimized for producing provisioning ecosystem services (ES) in the past few decades, often at the expense of regulating and cultural services. Research has focused mainly on the supply side of ES and related trade-offs, but the demand side for regulatory services remains largely neglected. The objective of this paper is to evaluate the usefulness of participatory geographic information system (PGIS) methods for demand assessment in larger rural and agrarian contexts by identifying spatially explicit demand patterns for ES, thereby enlarging the body of participatory approaches to ES-based land use management. Accordingly, we map, assess, and statistically and spatially analyze different demands for five ES by different stakeholder groups in agricultural landscapes in three case studies. The results are presented in a stakeholder workshop and prerequisites for collaborative ES management are discussed. Our results show that poor correlation exists between stakeholder groups and demands for ES; however, arable land constitutes the highest share of the mapped area of demands for the five ES. These results have been validated by both the survey and the stakeholder workshop. Our study concludes that PGIS represents a useful tool to link demand assessments and landscape management systematically, especially for decision support systems.

A rational assessment of electricity generation technologies constitutes a cornerstone to attain a sustainable and secure electricity plan. The Egyptian government is struggling with the accelerated growth of the national electricity demand through setting up and examining different future electricity scenarios and through the implementation of energy models to secure the provision of affordable and clean energy as part of the United Nations 2030 agenda of achieving the 17 sustainable development goals (SDGs). However, conventional techno-economic models still represent for many countries an attractive tool for energy planning. We investigate in this article the added values of applying a dynamic multi-criteria spatial-agent model that covers several sustainability dimensions versus an optimization techno-economic model for future energy planning in Egypt. Moreover, we report on the historical development of electricity supply since 2009 in Egypt. The study reveals predominant advantages of applying the agent-based modeling approach, which simulates the evolution of an energy transition landscape through the interactive and adaptive dynamic decision behavior of different societal groups (agents) in response to changes in the whole system. The study advocates the implementation of a dynamic agent-based bottom-up approach for the planning of a future sustainable electricity mix in Egypt.