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The Restoration Diagnostic is a three-step guide developed by the World Resources Institute (WRI) to increase the success rate of forest landscape restoration (FLR). By analyzing 16 historical case studies and peer-reviewed literature, WRI identified a suite of 'key success factors' categorized into three themes: motivation, enabling conditions, and implementation capacity. The diagnostic allows users to define a geographic scope, assess the status of these factors (in place, partly in place, or missing), and develop targeted strategies to close identified gaps. The tool is designed for mid-level managers in government, NGOs, and the private sector and serves as a component of the broader Restoration Opportunities Assessment Methodology (ROAM).

The document explains how 'Extreme Event Attribution' research determines the extent to which climate change makes specific weather events more likely or intense. It warns journalists against three common errors: ignoring climate change, attributing events without evidence, or naming it as the sole cause. The guide provides detailed scientific contexts for heatwaves, floods, tropical cyclones, heavy snowfall, droughts, and wildfires, noting that while some links (like heatwaves) are globally certain, others (like droughts or snowfall) are more complex and region-specific.

The document explains the methodology of 'extreme event attribution' to help journalists avoid common errors, such as ignoring climate change or attributing an event to it as a sole cause. It details how scientists use climate models to compare the modern world with a pre-industrial one to determine if an event was more likely or intense due to global warming. The guide provides specific scientific consensus and limitations for heatwaves, floods, tropical cyclones, heavy snowfall, droughts, and wildfires, emphasizing that while some connections are robust (e.g., heatwaves), others are more complex and depend on regional data and human vulnerability.

The document explains the science of extreme event attribution, detailing how researchers use climate models and historical data to determine if climate change made a specific event more likely or intense. It provides specific guidance on reporting various phenomena—heatwaves, floods, tropical cyclones, snowfall, droughts, and wildfires—highlighting where scientific confidence is high and where uncertainties remain.

The document explains 'extreme event attribution'—the scientific process of determining how climate change affects the likelihood and intensity of specific weather events. It provides a framework for journalists to avoid common reporting errors, such as ignoring climate change or attributing an event to it without evidence. The guide details the specific influence of global warming on heatwaves, floods, tropical cyclones, heavy snowfall, droughts, and wildfires, noting that while some links (like heatwaves) are globally certain, others (like droughts and floods) vary by region and are influenced by socio-economic vulnerabilities.

The document explains how 'attribution' studies determine if global warming increased the likelihood or intensity of a specific extreme weather event. It warns journalists against three common errors: ignoring climate change, claiming it caused an event without evidence, or treating it as the sole cause. The guide provides specific findings for heatwaves, floods, tropical cyclones, heavy snowfall, droughts, and wildfires, noting that while heatwaves are globally linked to warming, other phenomena like droughts and floods vary significantly by region.

The document explains the science of 'extreme event attribution,' which calculates how much climate change increases the probability or intensity of specific weather events. It warns journalists against three common errors: ignoring climate links, asserting links without evidence, or citing climate change as the sole cause. The guide provides specific scientific consensus and attribution examples for heatwaves, floods, tropical cyclones, heavy snow, droughts, and wildfires, emphasizing that while some events (like heatwaves) have a very strong global link to warming, others (like droughts or cyclones) are more complex and vary by region.

The guide argues that traditional linear problem-solving is insufficient for the complex, interlinked nature of global environmental and social crises. It introduces a four-phase framework for systems change—laying a foundation, understanding the system, committing to a desired future, and bridging the gap—supported by eight principles of practice. These principles emphasize mindfulness, co-creation, iterative experimentation, and the identification of deep leverage points to shift system structures and behaviors toward a sustainable and equitable future.

The document outlines various methodologies for 'situation analysis' to help conservation practitioners understand how corruption, power dynamics, and systemic risks can derail project implementation. It categorizes these approaches into broad systemic analyses—such as Political Economy Analysis (PEA), Political Ecology, and Corruption Risk Assessments (CRA)—and focused techniques like stakeholder and value chain analysis. The guide emphasizes that the most effective analysis is one that is manageable within available resources and directly informs programming through a 'thinking and working politically' approach, including the use of Everyday Political Analysis (EPA) to adapt to changing contexts.