Multi-Criteria Analysis (MCA) is a decision-making tool developed for complex problems. In a situation where multiple criteria are involved confusion can arise if a logical, well-structured decision-making process is not followed. Another difficulty in decision making is that reaching a general consensus in a multidisciplinary team can be very difficult to achieve. By using MCA the members don’t have to agree on the relative importance of the Criteria or the rankings of the alternatives. Each member enters his or her own judgements, and makes a distinct, identifiable contribution to a jointly reached conclusion. This manual is written for an audience that needs a clear, easy to follow manual that can be used in the field to implement MCA. The information is structured so that the reader is first introduced to the general concepts involved before dwelving into the more specific applications of Multi Criteria Analysis. The manual reviews the conceptual framework of C&I and introduces the theoretical basis of MCA, and methods such as ranking, rating and pairwise comparisons in the Analytic Hierarchy Process (AHP). It provides an example of how MCA can be applied to C&I in a Forest Certification context both from a ‘top-down’ perspective as well as in a more ‘bottom-up’ context.
Tag: Decision-making
Knowledge is power: Enhancing data for action on women’s rights, equality, and environmental sustainability via the Environment and Gender Index (EGI)
IUCN’s Environment and Gender Index (EGI) monitors progress toward gender equality and women’s empowerment in the environmental arena, holding governments and policy makers accountable. Existing knowledge can effectively inform national gender and environment policies and their implementation, bridging data gaps and overcoming barriers, to formulate best practices for using sex-disaggregated data and establishing a way forward.
Full-merged PDF also available in Gender and Climate Change : evidence and experience
The challenges of effective model scoping: a FLORES case study from the Mafungausti forest margins, Zimbabwe
This paper explores the challenge of defining the scope of a systems model, emphasising three aspects: boundary, granularity and conceptual scope. The significance of these is illustrated by reference to a model of land-use decisions made in villages bordering on the Mafungautsi forest in zimbabwe. The purpose of this model was to help policy players (Forestry Commission staff, non-governmental organisations, researchers and local people) to understand the impact of policy interventions on local people’s livelihoods. Scoping decisions that were made in building the Mafungautsi model were deliberately liberal, to encompass the inerests of all participants in the modelling process. These decisions now present a range of serious challenges: the difficulty of model calibration, the computational expense of running simulations, and the difficulty for new users to understand the model. Facilitators of modelling teams need to consider the serious implications of giving everyone what they want and including all participants’ ideas in a model. In the long run, it may be better to be tough and reject many suggestions at the outset. The former approach is unlikely to lead to a tractable model, while the latter may ultimately offer greater satisfaction for all.
Advancing landscape sustainability science: key challenges and strategies for integration with landscape design and planning
Advancing landscape sustainability science (LSS) is fundamental for guiding and navigating human development within safe and just Earth system boundaries. As a place-based and use-inspired science, LSS aims to understand and improve the sustainability of regional landscapes for both nature and people. It has evolved rapidly over the past decades, garnering increasing traction in landscape management, governance, and environmental decision-making. Because LSS can link local actions to regional and global contexts, it is critical for exploring transitions and transformation towards resilience and sustainability. However, in this era of profound human-induced environmental challenges and intertwined polycrisis, how LSS research translates into landscape design and planning practice through transdisciplinary frameworks, knowledge co-production processes, and science–action fusion is yet to be adequately addressed. Here, we first discuss the pressing needs to make landscape design and planning integral to LSS and then examine multifaceted challenges to achieve such integration, including research–practice, communication, implementation, multi-stakeholder, scale, and data and modelling barriers. Finally, we conclude with six key considerations to inform future research and practice that aim to integrate landscape design and planning in LSS so as to foster actionable knowledge co-production and shape transformative changes towards more sustainable and resilient landscapes.
Approaches to replenishing soil fertility in Africa: NGO perspectives
This report summarizes the output of a workshop whose main objectives were: – to bring together representatives from NGOs and other institutions working on the problem of declining soil fertility in Africa; – to take stock of the problem and review current approaches used to combat declining soil fertility; and to agree on and recommend priorities and cooperative approaches for tackling the problem. The report also provides a summary of the presentations, the discussions of the working groups and the Plan of Action that emerged from them.
Choosing between native and introduced tree species when planting
Key messages
- Both native and introduced tree species are important for planting, but the choice of which category to plant depends on the desired products and ecosystem services, the location and the planters themselves.
- Global planting initiatives are making an increased effort to include a wider range of native trees. This is to counter the current focus on a narrow species base, which leaves planted trees susceptible to system shocks and may impact the supply of tree products and services, and reflects a greater focus on tree planting for ecological restoration.
- This brief presents pros and cons for planting native and introduced tree species, and explores bottlenecks in the use of native trees for planting.
- Important measures to address these bottlenecks include making high-quality seeds and seedlings more available for planting, as well as developing and sharing decision-support tools to better target planting, improve tree management and ensure more effective use.
The ongoing journey of modelling intercropping systems: A conceptual resource sharing intercomparison from model developers and expert users
Context
The global shift toward sustainable agriculture has increased interest in using process-based models to design and optimize intercropping systems. However, these models differ fundamentally in how they represent trade-offs (competition for light, water, and nutrients) and synergies (facilitation, complementarity) in resource sharing between species. This conceptual variation creates uncertainty in model selection and application, particularly since most models were originally developed for monoculture and subsequently adapted for intercropping.
Objective
In this study, we describe how current crop models represent interspecies resource-sharing mechanisms, analyse their structural differences, and synthesize findings from existing validation studies to understand how their structural differences affect model performance. The models examined include APSIM (APSIM-Canopy, APSIM-Micromet, APSIM-Strip, APSIM-Alternating, APSIM-APSwim, APSIM-SoilArbitrator), DayCent, DSSAT-Mixed, DSSAT-MPI, LandscapeDNDC, LUCIA, MONICA, SIMPLACE Lintul5-Intercrop, STICS-Big-Leaf, STICS-Multilayer, and WaNuLCAS.
Methods
Through the Agricultural Model Intercomparison and Improvement Project (AgMIP) platform, we engaged with model developers and expert users to collect detailed information on how crop models represent intercropping systems using structured interviews and questionnaires. We then developed a framework that groups models by their core conceptual approaches to simulating resource sharing. Finally, we synthesize findings from existing quantitative validation studies to connect conceptual intercomparison to predictive performance across different intercrop characteristics and environments.
Results and Conclusions
Our analysis identifies six distinct conceptual approaches for simulating light sharing and four for belowground resource (water and nutrient) competition. Intercrop models show greater structural divergence in canopy than in belowground representation. Furthermore, competitive trade-offs (light, water, and nutrients) are widely represented while facilitative and other complex processes like N₂-fixation, plasticity (shoot and root), microclimate effects or hydraulic lift are often simplified or omitted. Our analysis of model validation studies reveals a critical trade-off: structurally complex models often perform well in simulating intercropping when calibration is done on sole crops, whereas simpler models require extensive intercrop-specific calibration to achieve better prediction performance. This distinction is vital for model application in data-scarce environments, as more complex architectures can leverage existing sole-crop data to effectively simulate intercrop systems. The classification of the structural resource capture differences in combination with the evaluated model performance analysis allowed us to devise an evidence-based model selection criteria framework useful also for for non-specialist, while the unique detailed description provided are highly valuable for the model research community.
Significance
This study establishes a conceptual framework that provides the necessary foundation for a meaningful quantitative intercomparison of intercrop models, as structural understanding enables the interpretation of numerical differences in model outputs. It also guides hypothesis testing, model choice, priorities in model development and improvements.
Stakeholder Engagement Approach to Risk-Informed and Evidence-Based Decision-Making (SHARED) Toolkit
The SHARED initiative serves as a cutting-edge resource for inclusive, evidence-based decision-making on complex development challenges. By bridging science, practice, and policy, SHARED fosters collaborative solutions through tailored facilitation, stakeholder engagement, and multi-sectoral partnerships. Its adaptable methodology emphasizes relationship dynamics, behaviours, and human decision-making, mobilizing interactive knowledge to strengthen cross-scale and cross-sectoral collaboration. Ultimately, SHARED promotes robust, evidence-driven processes that advance sustainability and equity, inviting stakeholders to join in shaping impactful outcomes.
Check also the facilitation guide here: Stakeholder Engagement Approach to Risk-Informed and Evidence-Based Decision-Making (SHARED) – Fundamentals of Facilitation
Stakeholder Engagement Approach to Risk-Informed and Evidence-Based Decision-Making (SHARED) – Fundamentals of Facilitation
The SHARED Fundamentals of Facilitation Guide complements the SHARED Toolkit by equipping facilitators with practical strategies for inclusive, evidence-based decision-making. Drawing on decades of facilitation experience and over 15 years of applying SHARED in agriculture and natural resource management, the manual introduces core principles, preparation techniques, and participatory approaches. It highlights the importance of powerful questions, effective session openings, and troubleshooting strategies to manage challenges. Designed for both new and experienced facilitators, the guide provides tools to confidently lead stakeholder engagement and strengthen collaborative governance through the SHARED Decision Hub Methodology.
See the toolkit here: Stakeholder Engagement Approach to Risk-Informed and Evidence-Based Decision-Making (SHARED) Toolkit
Online Course: Stakeholder Engagement with Evidence
Decision-making in landscapes and socio ecological systems is rarely straightforward. Challenges such as land degradation, competing land uses, and balancing conservation with development exist within constantly shifting policy, social, economic and environmental contexts.
To make decisions that endure, we need the right people at the table and the right evidence in the room. Stakeholder engagement is essential. Decisions made in isolation often fail to take root. By working collaboratively bringing together diverse knowledge, experiences, and perspectives we can build decisions that are more inclusive, evidence-informed, and sustainable.
The Stakeholder Approach to Risk Informed and Evidence-Based Decision-Making (SHARED), developed by CIFOR-ICRAF, offers a valuable framework to guide this process. By combining participatory engagement, systems thinking, and data-driven insights, the SHARED approach supports stakeholders to co-create solutions.