FAO

Connect with the videos, lecture notes and ongoing conversations from the massive open online course (MOOC) on National Adaptation Plans: Building Climate Resilience in Agriculture in this comprehensive online toolkit. Materials presented here were originally shared via the One UN Climate Change Learning Partnership Platform (UNCC:Learn) Platform during a six-week MOOC. The course is still available for self-paced learning on UNCC:Learn. The NAP-MOOC learning materials are presented as part of the Integrating Agriculture in National Adaptation Plans (NAP-AG) Programme and are a joint effort between the United Nations Development Programme (UNDP), the Food and Agriculture Organization of the United Nations (FAO), the United Nations Institute for Training and Research (UNITAR), and more than 40 leading experts on climate change, finance, agriculture, communications and more.

The joint UNDP-FAO Integrating Agriculture in National Adaptation Plans (NAP-Ag) Programme supports partner countries to identify and integrate climate adaptation measures for the agricultural sectors into relevant national planning and budgeting processes.

This course provides a definition of vulnerability and illustrates the three critical dimensions used to define it. It also presents the most commonly used methods to assess vulnerability, and provides examples and criteria for selecting the appropriate vulnerability indicators.

You will learn about

• The concept of vulnerability
• Using vulnerability assessments for decision making
• Tools available for conducting vulnerability assessments
• Selecting vulnerability indicators

This course is part of a series which introduces the FAO damage and loss methodology, developed to support countries to generate precise and holistic data for the agricultural sector, in response to climate- and weather-related disasters.

This course introduces the formulas which are used to compute damage and loss in the agricultural sectors (crops, livestock, forestry, aquaculture and fisheries). It then considers the data requirements and possible sources, and how the data can be used both to report on Sendai and Sustainable Development Goal (SDG) targets, and at national level.

You will learn about

• The key concepts of the FAO Damage and Loss methodology – production damage, production loss and asset damage
• How these are calculated in five agricultural sectors – crops, livestock, forestry, aquaculture and fisheries
• Data requirements, sources and collection methods for calculation of damage and loss using the methodology
• The importance of institutional collaboration for data collection and analysis
• How the D&L data can be used at global level in the Sendai Framework Monitor, and to inform national level policy making and planning

Agriculture is a risky sector. Extreme weather conditions, pests and diseases and market uncertainties are just few examples of events that can negatively affect farming activities, posing a major threat to households livelihood and food security. This course will present an overview of concepts linked to agricultural risk management, describing which risks farmers face, within a holistic approach that covers the entire agrifood system.

You will learn about

• Different risks affecting farming activities and their characteristics and main causes
• Implications of agricultural risks to farmers and other stakeholders in the agrifood system
• A holistic approach to risk management in agriculture
• Managing risks to improve livelihood and food security

This course focuses on Sustainable Land Management (SLM) practices, and their place within the global development agenda, specifically in order to achieve target 15.3 of the Sustainable Development Goals (SDGs), which aims "to achieve a land degradation-neutral world". The course assists policy makers, practitioners and land users in the selection, planning, implementation and monitoring of SLM interventions, and related enabling environment.

You will learn about

• Basic definitions and principles of land management, degradation and restoration
• The participatory SLM land use planning approach
• SLM tools and methods (WOCAT global network, the Economics of Land Degradation (ELD) initiative and their 6+1 approach)
• The use of financial and non-financial incentives for an enabling environment, to overcome barriers and encourage SLM adoption and uptake
• SLM in the context of the global policy agenda, specifically SDG goal 15
• The concept of Land Degradation Neutrality (LDN)

This course describes how the information derived from remote sensing is obtained and best used for crop monitoring in a food security context. It outlines what the exact meanings of the products are and shows how their early warning and food availability information contents can be combined efficiently with other sources (e.g. households surveys, market analyses, nutritional surveys, etc.).

This course has been developed as part of the EU-FAO Programme on "Improved Global Governance for Hunger Reduction" and the technical contents have been provided by the Joint Research Centre of the European Commission.

You will learn about

• Data sources and products used for remote sensing analysis of crop monitoring
• Calculation and evaluation of anomalies derived from rainfall and Normalized Difference Vegetation Index (NDVI)
• Production of seasonal graphs for rainfall and NDVI
• Phenological stages in the over-time analysis of crop conditions
• Creating, maintaining and archiving remote sensing images
• Most common software for processing remote sensing data

The e-learning tool 'Planning for Community Based Adaptation (CBA) to Climate Change' supports training on community-based climate change adaptation in agriculture. The tool links research-based knowledge on climate change impacts with examples and experiences on CBA drawn from FAO field projects and a range of country-specific case studies. The intended outcoume of the tool is to assist all actors, who face the challenge of initiating and facilitating adaptation processes at community level.

This course explains the concepts of food and nutrition, malnutrition, food security and livelihoods. Understanding these concepts is important to assess the nutrition situation, design and implement programmes, investments and policies that address nutrition problems (also called “nutrition-sensitive”), and evaluate the nutritional outcomes of programmes, investments and policies

You will learn about

• Food and Nutrition related concepts and definitions
• Nutrient requirements and balanced diet
• Different forms of malnutrition
• Causes of malnutrition
• Food Security and Livelihoods

This course covers the techniques for spatial data acquisition, spatial analysis, modelling, integration of various data sources and sharing spatial information (international standards and interoperability, spatial data infrastructure).

You will learn about

• How spatial data can help improve the quality and scope of activities in organizational processes
• Methods to obtain spatial data and systems for producing spatial information
• Interoperability and standards for sharing spatial data
• Technology behind spatial data infrastructure
• Techniques to disseminate spatial data

Degradation of forests and landscapes impacts the global climate, and also the food security and livelihoods of communities. Forest and landscape restoration (FLR) is a process which brings stakeholders together to create healthy, resilient and productive landscapes and meet national, regional and global commitments.​ This course has been developed to introduce the key concepts and process of forest and landscape restoration.

You will learn about:

• The importance of FLR and its key concepts​
• The benefits of FLR and how it helps countries to achieve their national, regional and global commitments​
• The three key steps of the FLR process
• The importance of engaging stakeholders in all steps of FLR and negotiating between potentially conflicting objectives.
• The various considerations when implementing, managing and monitoring FLR​
• Barriers and success factors for FLR