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This article discusses the importance of reproducibility in vegetation research and the role of data and code sharing in achieving this. The International Association for Vegetation Science (IAVS) has implemented a mandatory "Data Availability Statement" in the Journal of Vegetation Science (JVS) and Applied Vegetation Science (AVS) to improve transparency and reproducibility. The article examines the availability and accessibility of data and code in these journals over the past 10 years and finds a significant increase in data availability since 2019, while code availability has increased more slowly. The authors suggest that more information and training on data and code sharing practices could further improve reproducibility. They also acknowledge the need to consider issues of governance, protection of local community knowledge, and equity in data use. The text discusses two articles that were considered as award candidates for the Journal of Vegetation Science. The first article by Léo Delalandre and his co-authors examines the response of different plant groups to management intensification in Mediterranean rangelands. They found that annuals and perennials responded differently to the management gradient, highlighting the importance of considering different plant groups in studies of trait-environment relationships. The second article by Nicola Alessi and colleagues addresses the effects of probabilistic versus preferential sampling on analytical results in vegetation science. They compared two data sets of forest vegetation plots and found that probabilistic sampling was better for estimating species richness and diversity, while preferential sampling was better for detecting forest-specialist [Extracted from the article]