This resource includes Stream Temperature, Intermittency, and Conductivity (STIC) data collected from the Talladega research watershed (outlet location: 33.76219799, -85.59550775) in the Talladega National Forest (Cleburne County, AL, USA). The watershed drains a non-perennial unnamed tributary of Pendergrass Creek, and contains 0.92 km^2 of mixed coniferous and deciduous forest in the Piedmont Upland physiographic province. Located near Anniston, AL, the watershed spans an elevation range from 345 to 456 m above sea level and is a tributary to the Coosa River (within the larger Mobile-Tombigbee basin). The region has a humid subtropical climate, with mean daily January and July air temperatures of 5.3°C and 25.3°C respectively, and mean annual precipitation of 1400 mm/yr.

These sensors were deployed specifically in support of the Talladega flow manipulation experiment, part of Approach 4 of the Aquatic Intermittency effects on Microbiomes in Streams (AIMS) Project. Briefly, a before-after-control-impact (BACI) experimental design was followed to assess the impacts of flow reduction and flow recovery on microbial communities and ecosystem processes. A small plywood dam and plastic drainage pipes were used to divert flow from an 85-m section of the stream. This resulted in two study reaches: 1, an impacted reach downstream of the dam, where flow is reduced when the dam is activated but recovers when the dam is deactivated, and 2, an un-impacted reference reach upstream of the dam where flow is not impacted by the damming. Within each reach, five transects (spaced ~15-m apart) were sampled at six time points, including before flow reduction (t1), during a 1-month-long flow reduction (t2, t3), and after flow recovery (t4-t6).

12 STIC loggers were placed along the experimental and control reaches (evenly divided between pools, riffles, and riparian zones along each reach. These sensors were set to collect temperature and conductivity data every 15 minutes from June 2, 2022, to October 17, 2022. The raw conductivity data were used to classify the timeseries into wet or dry readings at each timestep. Each .csv file is associated with a single site for a single year. Also included is a “ReadMe” file that includes author information, column descriptions, and site locations. More information can be found on the AIMS OSF site: https://osf.io/e7s9j/