[4] emphasize the need to embrace variability and context dependency in judging restoration success across multidimensional ecological indicators. They highlight major knowledge gaps regarding long-term trajectories, landscape factors, and integrating socioeconomic considerations. A global meta-analysis by [PERSON] et al. [9] determines key biophysical and anthropogenic factors influencing restoration success for forests, including climate, previous land use intensity, and herbivory. [PERSON] et al. [19] review the criteria for evaluating restoration outcomes and call for standardized indicators encompassing ecosystem services. Recent studies also elucidate factors influencing restoration outcomes across habitat types and biome boundaries. In tropical forests, passive restoration has proven more effective than tree planting for biodiversity recovery [6; 9]. However, active interventions may still be needed in certain contexts and cost-effective techniques require further research [9]. For riparian zones, revegetation success depends on climate, topography, channel dynamics, and flooding regimes [20; 21]. Outcomes also vary with landscape factors like adjacent land use and connectivity [9]. Studies clarifying how biotic and abiotic controls interact across spatial scales are lacking. Several key knowledge gaps persist regarding vegetation restoration. Plant and animal colonization dynamics during restoration are poorly characterized, limiting understanding of community assembly patterns [4]. Long-term studies tracking soil development trajectories are scarce, precluding assessment of time lags [7]. Landscape context effects on local restoration outcomes need elaboration, including edge influence, fragmentation, and metapopulation source-sink dynamics [9]. Integrating socioeconomic factors into planning remains a challenge, such as cost-benefit analysis and stakeholder participation [19]. Developing standardized criteria and indicators for systematic evaluation across sites and ecosystem types is also essential [19]. To address these knowledge gaps, a global network of coordinated, long-term, interdisciplinary studies is critically needed to elucidate restoration outcomes across contexts. By linking restoration practices to multivariate ecological responses over decades, this research network could provide integrated guidelines to maximize restoration success. It is crucial to continue focusing on the connection between restoration practices, environmental factors, and multivariate outcomes in order to understand the dependencies on context [4]. Conducting systematic experiments that test different restoration methods across various biomes can help unveil general principles while taking into account landscape variation [9]. Additionally, it is essential to extend monitoring efforts to capture slower responses such as plant colonization and soil development, but this will require sustained funding [7; 9]. Techniques such as remote sensing, geospatial modeling, and simulation approaches can shed light on the effects of scale on restoration outcomes [9]. When planning and assessing restoration efforts, it is important to incorporate socioeconomic factors and standardize criteria for evaluating success [19; 22]. The priorities of different research directions can be ranked in the following order of importance:  
1. Standardize criteria and indicators for systematic meta-analysis across diverse studies: Standardizing criteria and indicators is crucial for conducting robust meta-analysis and synthesis of restoration research. By establishing consistent guidelines, researchers can clarify general principles and enhance the reliability of their findings. This will facilitate the integration of diverse studies and provide a stronger evidence base for restoration practices. (Top Priority)
2. Establish coordinated research networks for long-term, interdisciplinary studies linking practices to ecological outcomes: Coordinated research networks are essential for managing long-term studies and fostering interdisciplinary collaborations.