Ecosystems in the Anthropocene face pressures from multiple, interacting forms of environmental change. These pressures, resulting from land use change, altered hydrologic regimes, and climate change, will likely change the synchrony of ecosystem processes as distinct components of ecosystems are impacted in different ways. However, discipline-specific definitions and ad hoc methods for identifying synchrony and asynchrony have limited broader synthesis of this concept among studies and across disciplines. Drawing on concepts from ecology, hydrology, geomorphology, and biogeochemistry, we offer a unifying definition of synchrony for ecosystem science and propose a classification framework for synchrony and asynchrony of ecosystem processes. This framework classifies the relationships among ecosystem processes according to five key aspects: 1) the focal variables or relationships representative of the ecosystem processes of interest, 2) the spatial and temporal domain of interest, 3) the structural attributes of drivers and focal processes, 4) consistency in the relationships over time, and 5) the degree of causality among focal processes. Using this classification framework, we identify and differentiate types of synchrony and asynchrony, thereby providing the basis for comparing among studies and across disciplines. We apply this classification framework to existing studies in the ecological, hydrologic, geomorphic, and biogeochemical literature, and discuss potential analytical tools that can be used to quantify synchronous and asynchronous processes. Furthermore, we seek to promote understanding of how different types of synchrony or asynchrony may shift in response to ongoing environmental change by providing a universal definition and explicit types and drivers with this framework.

Streamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed-scale processes. When stream gages read zero, this may indicate that the stream has fully dried; however, zero-flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero-flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero-flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human-driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero-flow interpretations. We also highlight additional methodss for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero-flow gage readings and implications for reach- and watershed-scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero-flows will only attain greater importance in a more variable and changing hydrologic climate.