Piezometers were installed in the fen around the pumping well with

screened sections completely below small molecule library screening the peat layer in the underlying coarse sand. The total depths (approximate measurement points) ranged from 25 to 315 cm bgs. Each piezometer consisted of a steel drive point with a 38 cm long screened section of 3 cm diameter schedule 80 steel pipe coupled to sections of unslotted steel pipe. The drive point and pipe were hammered to the desired depth using a post-pounder striking a drive cap. The location and elevation of all monitoring wells and piezometers, and ground surface topography were surveyed using a TOPCON® total station. The survey data were used to calculate water level elevations and to develop a detailed representation of the land surface. The wells and piezometers were instrumented with pressure transducers (Global Water GL-15 and Onset Hobo Level Logger) that recorded water level at fixed time intervals of 5, 30, or 60 min, depending on the season and application. Non-vented loggers

were corrected for atmospheric pressure using data from an on-site barometric pressure data logger. See Table 2 for a complete description of the physical properties of the wells and piezometers. We analyzed vegetation composition in a 1 m radius circular plot around each monitoring well/piezometer nest. In each plot a complete list of vascular plants and bryophytes was made, and the canopy coverage, by species, was estimated. The percent cover of plant species occurring at 17 well locations was analyzed to determine the correlation with hydrologic parameters and peat thickness check details using Canonical Correspondence Analysis, CCA (McCune and Mefford, 2012). Two hydrologic variables were used, the highest water table elevation during the very dry 2004 growing Tau-protein kinase season (July–September), and the lowest water table during the very wet 2005 growing season. These were selected because; (1) the maintenance of a high water table in a dry year is critical for supporting peat and fen vegetation, and (2) deep water table drawdowns

in a wet year would be indicative of an abnormal impact such as pumping drawdown. Distance from each plot to the Crane Flat pumping well is shown on the CCA diagram as unique symbols, but distance was not used in the CCA calculation. The CCA axes were calculated as linear combinations of the hydrologic parameters and peat thickness for each plot. Vegetation data displayed on the ordination include the plot location relative to other plots and plant species centroids, which is the average position of species along the axes based on their abundance at each well. To evaluate the statistical significance of the CCA, we ran a 9998-iteration Monte Carlo test that randomly reassigned the environmental data to different plots. The proportion of Monte Carlo outcomes with an axis-1 eigenvalue greater than the observed eigenvalue is the p-value for the CCA.