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Abstract Knowledge Graphs organize and connect disparate data for integrating information in a user‐friendly interface for recommendations and applications. This analytical tool for supporting data interrogation has not been widely applied in agronomy. This article focuses on Knowledge Graph applicability and specifically the utility of the recently released Esri ArcGIS Knowledge platform for identifying system resilience using a community‐driven database (Forage Data Hub; 52,997 entries from 108 unique locations over 51 years) comprising legacy datasets encompassing multiple temporal and spatial scales. Overall, perennial systems had greater drought risk resilience estimates (DRRE) than annuals, with alfalfa (Medicago sativa) having a “very high” DRRE across ecoregions. Knowledge Graphs provided information on how geography and agronomic systems interact to impact resilience. Results can be used to design agricultural systems within specific geographic locations with greater resilience and stability in the face of a changing climate per geographic region. 

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under- sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.