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Abstract The general public and scientific community alike are abuzz over the release of ChatGPT and GPT-4. Among many concerns being raised about the emergence and widespread use of tools based on large language models (LLMs) is the potential for them to propagate biases and inequities. We hope to open a conversation within the environmental data science community to encourage the circumspect and responsible use of LLMs. Here, we pose a series of questions aimed at fostering discussion and initiating a larger dialogue. To improve literacy on these tools, we provide background information on the LLMs that underpin tools like ChatGPT. We identify key areas in research and teaching in environmental data science where these tools may be applied, and discuss limitations to their use and points of concern. We also discuss ethical considerations surrounding the use of LLMs to ensure that as environmental data scientists, researchers, and instructors, we can make well-considered and informed choices about engagement with these tools. Our goal is to spark forward-looking discussion and research on how as a community we can responsibly integrate generative AI technologies into our work. 

Abstract High‐altitude tropical grasslands, known as “páramos,” are characterized by high solar radiation, high precipitation, and low temperature. They also exhibit some of the highest ecosystem carbon stocks per unit area on Earth. Recent observations have shown that páramos may be a net source of CO₂to the atmosphere as a result of climate change; however, little is known about the source of this excess CO₂in these mountainous environments or which landscape components contribute the most CO₂. We evaluated the spatial and temporal variability of surface CO₂fluxes to the atmosphere from adjacent terrestrial and aquatic environments in a high‐altitude catchment of Ecuador, based on a suite of field measurements performed during the wet season. Our findings revealed the importance of hydrologic dynamics in regulating the magnitude and likely fate of dissolved carbon in the stream. While headwater catchments are known to contribute disproportionately larger amounts of carbon to the atmosphere than their downstream counterparts, our study highlights the spatial heterogeneity of CO₂fluxes within and between aquatic and terrestrial landscape elements in headwater catchments of complex topography. Our findings revealed that CO₂evasion from stream surfaces was up to an order of magnitude greater than soil CO₂efflux from the adjacent terrestrial environment. Stream carbon flux to the atmosphere appeared to be transport limited (i.e., controlled by flow characteristics, turbulent flow, and water velocity) in the upper reaches of the stream, and source limited (i.e., controlled by CO₂and carbon availability) in the lower reaches of the stream. A 4‐m waterfall along the channel accounted for up to 35% of the total evasion observed along a 250‐m stream reach. These findings represent a first step in understanding ecosystem carbon cycling at the interface of terrestrial and aquatic ecosystems in high‐altitude, tropical, headwater catchments.