DOI: 10.5061/dryad.r4xgxd28j
title: Carbon fixation by photosynthetic mats along a temperature gradient in a Tengchong hot spring

description: Geothermal hot springs, widely distributed on Earth, are important
 geological green-house gas sources which contribute large amounts of
 CO2 emission to the atmosphere. Exploring microbial carbon
 fixation in these springs is vital to fully understand the carbon budget
 in these terrestrial aquatic systems. In this study, carbon fixation rate
 by photosynthetic mats was determined with a 13C labeling
 approach along a gradient of temperature (~69 - ~75 oC) in a
 geothermal pool at Rehai Park in Tengchong, Yunnan Province, China. Light
 experiments were performed to determine carbon fixation rate by both
 photosynthesis and chemosynthesis, while dark experiments were performed
 by chemosynthesis. The results showed that the highest carbon fixation
 rate (about 4,637 μg C/g TOC/h) was obtained in light at the lowest
 temperature (~69 oC) in the afternoon (1:00 to 6:00 pm), most of
 which (96.7%) was contributed by photosynthesis. The lowest carbon
 fixation rate (138 μg C/g TOC/h) was measured at the highest temperature
 (~75 oC), where chemosynthesis dominated over photosynthesis in
 carbon fixation. At these rates, the photosynthetic mats would fix 80%
 CO2 emission during the daytime. At the end of daytime, the
 photosynthetic mats respired 34% -70% newly fixed organic carbon in one
 hour. Interestingly, both the carbon fixation rate and respiration rate
 decreased exponentially with increasing temperature, which may be ascribed
 to a temperature dependence of both microbial community composition and
 enzymatic activity. In summary, our study revealed that biological carbon
 fixation by photosynthetic mats is highly temperature dependent and
 significantly affects carbon cycling in hot springs.  
description: File of 13C-Raw data.xlsx To measure
 the δ<sup>13</sup>C values of organic carbon, all samples were
 thawed at room temperature and centrifuged at 10,000 rpm for 15 minutes to
 collect the solid (biomass and sediment). The samples were acidified with
 1 mM HCl overnight to remove inorganic carbon. The acidified samples were
 washed with deionized water to neutralize pH, and then dried at 50 ºC
 overnight. The dried solid samples were homogenized and weighted into
 sealed tin cups. δ<sup>13</sup>C values were measured twice
 for each sample with a Picarro iTOC-CRDS isotope analyzer.
 File of DRCB.fasta About 15 ml mat and surface
 sediment samples were collected for microbial community analysis. Samples
 were collected from sites DRCB-1, DRCB-2, DRCB-3, DRCB-4, DRCB-5 with
 sterilized spoons, and transferred into 50 ml polypropylene tubes. Genomic
 DNA was extracted from 0.5 wet sample using the FastDNA SPIN Kit (MP
 Biomedical, Solon, OH, USA) according to manufacturer’s protocol (Hou et
 al., 2013). PCR amplification was conducted with modified primers 515F
 (5’-GTG YCA GCM GCC GCG GTA A-3’) and 806R (5’-GGA CTA CHV GGG TWT CTA
 AT-3’) designed to be universal for bacteria and archaea (Caporaso et al.,
 2011; Caporaso et al., 2012). In order to identify individual samples from
 the reads, unique 8-bp barcodes were added at the 5′-end of both the
 forward and reverse primers. PCR products were purified following
 previously published literature (Hou et al., 2013). All PCR products were
 pooled together with equal molar amounts. Illumina MiSeq sequencing was
 performed with the MiSeq Reagent Kit v2 2× 250 bp.
 Sequence demultiplexing and quality control were performed with
 Cutadapt 1.9.1 (Martin, 2011). The sequences that had an average quality
 score of lower than 27 were removed from subsequent analysis. Operational
 taxonomic unit (OTU) cluster at 97% sequence identity was determined by
 using UCLUST algorithm (Edgar, 2010). The first sequence from each OTU was
 picked as a representative, and taxonomy was assigned to each
 representative using the ribosome database project (RDP) classifier
 algorithm (Wang et al., 2007). Sequences that could not be classified with
 this algorithm were manually searched against the NCBI BLAST database
 using BlastN to find highly similar hits.