Space-for-Time-Substitution surveys (SFTS) are commonly used to describe zooplankton community dynamics and to determine lake ecosystem health. SFTS surveys typically combine single point observations from many lakes to evaluate the response of zooplankton community structure and dynamics (e.g., species abundance and biomass, diversity, demographics and modeled rate processes) to spatial gradients in hypothesized environmental drivers (e.g., temperature, nutrients, predation), in lieu of tracking such responses over long time scales. However, the reliability and reproducibility of SFTS zooplankton surveys have not yet been comprehensively tested against empirically-based community dynamics from longterm monitoring efforts distributed worldwide. We use a recently compiled global data set of more than 100 lake zooplankton time series to test whether SFTS surveys can accurately capture zooplankton diversity, and the hypothesized relationship with temperature, using simulated SFTS surveys of the time series data. Specifically, we asked: (1) to what degree can SFTS surveys capture observed biodiversity dynamics; (2) how does timing and duration of sampling affect detected biodiversity patterns; (3) does biodiversity ubiquitously increase with temperature across lakes, or vary by climate zone or lake type; and (4) do results from SFTS surveys produce comparable biodiversity-temperature relationship(s) to empirical data within and among lakes? Testing biodiversity-ecosystem function (BEF) relationships, and the drivers of such relationships, requires a solid data basis. Our work provides a global perspective on the design and usefulness of (long-term) zooplankton monitoring programs and how much confidence we can place in the zooplankton biodiversity patterns observed from SFTS surveys