DOI: 10.4211/hs.6bde27bce59044e9881eb35844efd230
title: Microbial sampling metadata from Konza prairie (KS, USA) stream synoptic (AIMS_GP_approach3_MIME)

description: This study surveyed leaf litter across a non-perennial stream system located within the South Fork of King’s Creek at Konza Prairie Biological Station. At the USGS gage located on the mainstem (06879560; est. 1979), Kings Creek is a 5th order intermittent stream draining 1059-ha of tallgrass prairie in the Kansas Flint Hills. 
Sample collection followed a synoptic survey design to support the sampling goals of the Aquatic Intermittency effects on Microbiomes in Streams (AIMS) Project. During June 2021, a field team co-collected datasets characterizing stream microbiota, biogeochemistry, and hydrology across 50 locations within a sub-drainage of the South Fork of Kings’ Creek. The 50 sites were selected to balance multiple competing priorities: (i) strategically targeting existing monitoring infrastructure with long-term data (n=14); (ii) including sites near several known springs and tributary junctions (n=9); and (iii) including a range of drainage area and topographic wetness index (TWI) values (n=27), both of which have been correlated with flow permanence elsewhere. For a detailed description of the site selection process, please see (Swenson et al., 2024).
Samples were collected during the period of June 4th to June 8th, 2021, following the AIMS Microbial Field Sampling protocol (Zeglin and Busch, 2024). Briefly, at each site, the microbial sampling field crew visually ascertained whether surface water was present at the site, classifying sites as 'wet' (n=45) or 'dry' (n=5). At the time of sampling the stream was divided into three subsampling areas (compartments) of equal width across the wetted width of the channel at wet sites, or across the inferred channel width at dry sites. At each site, one leaf was collected randomly from each of the three sampling compartments. Where there was no leaf litter located directly within a subsampling area, leaf litter up to 2-m upstream of the transect was sampled, or beyond 2-m no leaf litter was sampled for that compartment. We avoided leaves that were too decomposed to be identifiable and also avoided green undecomposed leaves. All sampled leaves were identified to the lowest possible taxonomic level. For subsequent data analysis, the leaf litter data from each site was converted to provide the binary presence/absence of leaf taxa within the sampling transect. In the binary coding scheme, most plant species were lumped to the genus level, but grasses and sedges were lumped to the order Poales. In some cases, leaves were only identified as 'unknown shrub' or 'unknown forb'. The leaves identified in this dataset correspond with the leaves collected for microbial analyses, i.e., EEA analysis, qPCR, 16SS and ITS rDNA metabarcoding. Presence/absence of a leaf type in this dataset corresponds with the presence/absence of a leaf type from the corresponding leaf DNA sample or leaf enzyme sample.

References:
Swenson, L. J., Zipper, S., Peterson, D. M., Jones, C. N., Burgin, A. J., Seybold, E., ... & Hatley, C. (2024). Changes in Water Age During Dry‐Down of a Non‐Perennial Stream. Water Resources Research, 60(1), e2023WR034623. https://doi.org/10.1029/2023WR034623
Zeglin, L., M. Busch (2024). AIMS SOP - Microbial Field Sampling, HydroShare, http://www.hydroshare.org/resource/4b071711215341118330c22f18b5d20d