Climate change is threatening plant health and productivity at all spatial scales. To date, it remains largely unknown whether plant breeding and agricultural management practices can keep pace with the rate and direction of environmental change, as well as species’ rate of adaptation to rapid environmental change. In addition, the incidence of invasive pests and pathogens is increasing as a consequence of globalization. This trend is being exacerbated by climate change. Thus, future plant health and productivity will depend on the match between genotypes (and their resulting phenotypes) and new environments. However, these analyses are challenging since they require the integration of diverse data types, usually decentralized and lacking in standardization: genotypic, phenotypic and environmental. Hence, centralized and up-to-date platforms which integrate, visualize and analyze high-throughput biological data are key, especially in the current big data era in plant biology. CartograPlant (https://cartograplant.org/) is a web-based application that integrates, visualizes, and analyzes genotypic, phenotypic, environmental data, and their associated metadata, from georeferenced plants. Environmental data is available through advanced integration of global and regional layers. The genotype and phenotype metrics are collected through direct submission of studies at the time of publication or through the biocuration efforts of the affiliated databases and applications (TreeGenes, BIEN, TreeSnap). Data analysis is enabled by accessing the metadata associated with the public studies and providing appropriate workflows through Galaxy (https://galaxyproject.org/). This metadata collection, using ontologies and standards, allows data integration and analysis coming from different studies, which is key to perform both mega and meta-analysis. Mega-analysis and meta-analysis of GWAS (GxP association) and landscape genomics (GxE association) studies can improve the power to detect association signals by increasing sample size and by examining more variants throughout the genome than each dataset alone. Thus, they allow users to answer unprecedented and ambitious adaptive questions, taking advantage of the potential of high-throughput biological data. This talk will describe the recent updates in data sources, functionalities, and analytic workflows offered by CartograPlant.