The combination of continuing anthropogenic impact on ecosystems across the globe and the observation of catastrophic shifts in some systems has generated substantial interest in understanding and predicting ecological tipping points. The recent establishment and full operation of NEON has created an opportunity for researchers to access extensive datasets monitoring the composition and functioning of a wide range of ecosystems. These data may be uniquely effective for studying regime shifts and tipping points in ecological systems because of their long time horizon, spatial extent, and most importantly the coordinated monitoring of many biotic and abiotic components of focal ecosystems. The variety of these data can capture a range of potential community shifts while also monitoring an extensive set of environmental drivers. This combination is critical for assessing whether changes are a result of external forcings or internal dynamics. Here, we present an overview of regime shift dynamics; describe a variety of approaches to identify tipping points with data from time series, spatial patterns, or frequency distributions of community states across environmental conditions; and suggest a number of NEON data products that may be appropriate for such analyses.