• Energy Research

Abstract Tropical mountain cloud forests (TMCF) harbour a high bryophyte (mosses and liverworts) biomass and diversity. Furthermore, the high air humidity makes these forests well suited for bryophyte‐associated nitrogen (N2) fixation by cyanobacteria, providing a potentially important source of N input to the ecosystem. However, few studies have assessed bryophyte‐associated N input in these ecosystems, and these have focused on epiphytic bryophytes, whereas abundant ground‐covering bryophytes have not been included. In this study, we quantified N2 fixation rates associated with bryophytes, focusing on ground‐covering mosses in a neotropical mountain cloud forest. Furthermore, we identified the effects of climate change (higher temperature 10 vs. 20° and lower bryophyte moisture level 50% vs. 100%) on N2 fixation across bryophyte species and groups (mosses and liverworts). Nitrogen fixation rates associated with ground‐covering moss species were up to 2 kg N ha−1 year−1, which is comparable to other N inputs (e.g. N deposition) in tropical cloud forests. Furthermore, changes in temperature showed little effect on N2 fixation, but low moisture levels significantly suppressed N2 fixation activity. We found low N2 fixation activity associated with the investigated liverworts. Our results demonstrate the importance of ground‐covering, moss‐associated N2 fixation as a N source in tropical cloud forests and suggest that predicted future declines in precipitation in these systems will reduce N inputs from bryophyte‐associated cyanobacteria. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Climate change alters frequencies and intensities of soil drying-rewetting and freezing-thawing cycles. These fluctuations affect soil water availability, a crucial driver of soil microbial activity. While these fluctuations are leaving imprints on soil microbiome structures, the question remains if the legacy of one type of weather fluctuation (e.g., drying-rewetting) affects the community response to the other (e.g., freezing-thawing). As both phenomenons give similar water availability fluctuations, we hypothesized that freezing-thawing and drying-rewetting cycles have similar effects on the soil microbiome. We tested this hypothesis by establishing targeted microcosm experiments. We created a legacy by exposing soil samples to a freezing-thawing or drying-rewetting cycle (phase 1), followed by an additional drying-rewetting or freezing-thawing cycle (phase 2). We measured soil respiration and analyzed soil microbiome structures. Across experiments, larger CO2 pulses and changes in microbiome structures were observed after rewetting than thawing. Drying-rewetting legacy affected the microbiome and CO2 emissions upon the following freezing-thawing cycle. Conversely, freezing-thawing legacy did not affect the microbial response to the drying-rewetting cycle. Our results suggest that drying-rewetting cycles have stronger effects on soil microbial communities and CO2 production than freezing-thawing cycles and that this pattern is mediated by sustained changes in soil microbiome structures.

Global warming is most pronounced in the Arctic region. Greenhouse gas (GHG) release from Arctic soils increase due to global warming. By this, the Arctic may change from currently being a carbon sink to a future source. To improve accurate predictions of future GHG release from Arctic soils, it is important to unravel factors controlling both the microbial community structure and activity. Soil microbial activity is important for Arctic greenhouse gas production, but depends on soil conditions such as salinity being increased by calcium (Ca) and decreased by amorphous silica (Si) potentially enhancing water availability. In the Arctic, climate changes may alter salinity by changing Si and Ca concentrations upon permafrost thaw as a result of global warming with Si potentially decreasing and Ca potentially increasing salinity. Here, we show that higher Si concentration increased and higher Ca concentrations decreased the microbial CO2 production for both a salt-poor and a salt-rich soil from Greenland. In the salt-rich soil, Si amendment increased CO2 production and the abundance of gram-negative bacteria. However, the bacterial community became dominated by spore-forming gram-positive Firmicutes and Actinobacteria. The CO2 release from soils was directly affected by the abundance of bacteria and fungi, and their community structure. Our results highlight the importance of the soil Si and Ca concentration on organic carbon turnover by strongly changing microbial abundance and community structure, with consequences for CO2 release in the Arctic. Consequently, Ca and Si and their relation to Arctic soil microbial community structure has to be considered when estimating pan-Arctic carbon budgets.

On 2014-09-10, a soil warming and irrigation experiment was set up at Kongsfjordneset on the Brogger Peninsula, Svalbard. It consists of 48 plots centred on individual frost boils treated with a factorial combination of warming with open top chambers and irrigation. The experimental design results in four OTC-irrigation treatments, each replicated 12 times across three blocks. The OTCs have a basal diameter of 1.04 m. The irrigation treatment consisted of applying 1 L of deionised water to 24 of the frost boils in mid-late June and late August each year, simulating c. 20 mm rainfall events. Frost boil temperatures were monitored by burying Tinytag Plus 2 loggers in soil in four chambered and four unchambered plots. The loggers recorded temperatures at a depth of 30-35 mm between 2014-09-10 and 2018-08-27. They were replaced yearly with newly calibrated units. Measurements recorded between September 2017 and August 2018 by two loggers that had become exposed at the soil surface in summer 2018 were deleted from the dataset. Gas exchange between the soil and atmosphere was measured twice in each of the 48 frost boils, on 2018-08-23 and 2018-08-26, using a closed loop system and a Piccaro Gas Analyzer. The analyzer was attached to a transparent polycarbonate chamber equipped with fans for air circulation seated on stainless steel frames that had been hammered into the soil in each boil on 2018-06-30. Gutters filled with water around each frame ensured an airtight seal. The chamber was covered with dark cloth to eliminate photosynthetically active radiation during the measurements. CO2 and CH4 exchange was measured over a period of 5 min. The fluxes of both gases were calculated by fitting 2nd order polynomial models to changes in gas concentrations over time. In order to avoid bias associated with the initial stabilization period and saturation towards the end of the measurements, only data measured from 50-250 sec were included in these calculations, and gas fluxes were calculated from slopes taken 100 sec after the start of each measurement. The copy number of bacterial 16S ribosomal RNA genes in DNA extracts from frost boil soil was measured in 20 µl reactions, consisting of 0.8 µl of each of the primers 341F (5'-CCTAYGGGRBGCASCAG-3') and 806R (5'-GGACTACHVGGGTWTCTAAT-3'),10 µl of 2 x qPCRBIO SyGreen Blue Mix Lo-ROX (PCR Biosystems Inc., Wayne, PA, USA), 2 µl of sample (diluted 10 times to avoid inhibition of PCR) and 6.4 µl of H2O. The PCR mixes were heated to 95 °C for 180 sec, and then subjected to 45 cycles of 95 °C for 5 sec and a final melt at 60 °C for 30 sec on LightCycler® 96 real-time PCR instrument. Fungal ITS2 copy numbers were measured in the same way, but with 0.8 µl of each of the primers ITS4 (5'-TTCCTSCGCTTATTGATATGC-3') and ITS7 (5'-GTGARTCATCGARTCTTTG-3') in 20 µl reactions. The measurements from one sample, for which the copy numbers of bacterial 16S ribosomal RNA genes and fungal ITS2 regions were 2-3 orders of magnitude lower than the other 47 samples, were deleted from the dataset. Copy numbers were expressed per g dry weight of soil (105 °C for 18 h). DNA extracted from soil was suspended in 50 µl of Tris-EDTA buffer. A universal eubacterial primer set, 331F (5'-TCCTACGGGAGGCAGCAGT-3')/ 797R (5'-GGACTACCAGGGTATCTAATCCTGTT-3'), was used to amplify V3-V4 hypervariable regions of the 16S ribosomal RNA gene with MiSeq adapters. Each PCR was carried out in a 50 µl reaction volume containing 2 x Premix Taq, 1 µM of each primer and 1 µl of DNA extract. PCR amplification was performed in a BioRad T100 thermal cycler with an initial denaturation step at 95 °C for 5 min, followed by 35 cycles of denaturation for 15 sec at 95 °C, annealing for 45 sec at 56 °C and elongation for 90 sec at 72 °C, and a final elongation step for 10 min at 72 °C. The PCR products were purified using AMPure XP beads and a second PCR step was performed to ligate unique dual-index adapters with each sample using a Nextera XT Index Kit v2. The second PCR step was performed in a 25 µl reaction volume containing 2 x Premix Taq, 5 µl of each index primer and 5 µl of each purified PCR product. The thermal cycling conditions were set to 95 °C for 3 min followed by eight cycles of 95 °C for 30 sec, 55 °C for 30 sec and 72 °C for 30 sec, with a final elongation step at 72 °C for 5 min. The final libraries were purified using AMPure XP beads in 30µl of 10 mM Tris-HCl (pH 8.5), and were pooled in equimolar concentrations (4 nM) before sequencing on an Illumina MiSeq sequencer. The demultiplexed raw sequence reads were trimmed with Trimmomatic version 0.35 using the settings SLIDINGWINDOW:4:5, MINLEN:36, and subsequently analyzed following the MiSeq SOP in mothur v1.40.5. The trimmed paired ends sequence reads were merged and a non-redundant collection of sequences was generated by binning identical sequences. The resulting unique sequences were aligned against a SILVA-based reference alignmentand sequences differing by up to two basepairs were preclustered. Chimeric sequences were detected using VSEARCH implementation in mothur and removed. The taxonomy of the high-quality 16S ribosomal RNA gene sequences was assigned against the EzBiocloud database. Sequences were clustered into OTUs at a 97% similarity cutoff using the OptiClust implementation in mothur. Data on CO2 and CH4 exchange rates between soil and atmosphere, soil temperatures, bacterial 16S ribosomal RNA genes, fungal internal transcribed spacer 2 (ITS2) copies and the relative abundances of the 40 most abundant bacterial taxa in the 48 plots of a soil warming and irrigation experiment on Svalbard in the High Arctic. On 2014-09-10, a soil warming and irrigation experiment was set up at Kongsfjordneset on the Brogger Peninsula, Svalbard. Warming was applied continuously with open top chambers and the irrigation treatment was applied in mid-late June and late August each year. Greenhouse gas exchange between the soil and atmosphere was measured on 2018-08-23 and 2018-08-26. At this time, soil samples were taken for DNA analyses and the amount of bacterial and fungal DNA present in soil was measured. The 40 most frequent bacterial operational taxonomic units were also determined. This project was funded by UK Natural Environment Research Council (core funding to the British Antarctic Survey), the Danish National Research Foundation (CENPERM DNRF100) and Seoul National University. Equipment Soil temperatures: Tinytag Plus 2 loggers (TGP-4017, Gemini Data Loggers Ltd., Chichester, UK) Greenhouse gas exchange: Piccaro Gas Analyzer (Picarro G4301, Santa Clara, CA, USA) Q-PCR assays: LightCycler 96 real-time PCR instrument (Roche Life Science, Hvidovre, Denmark) PCR amplification: BioRad T100 thermal cycler (Bio-Rad Laboratories, Inc., Hercules, CA, USA) DNA barcoding: Illumina MiSeq sequencer (Illumina, Inc., San Diego, CA, USA) Software Trimmomatic version v. 0.35 mothur v1.40.5 Temperature data are the means derived from loggers in four unchambered plots and in four chambered plots. Gas exchange data are means of two measurements taken from each plot on 2018-08-23 and 2018-08-26. Missing data are indicated by NA.