Microbiogeochemical Traits to Identify Nitrogen Hotspots in Permafrost Regions
Abstract
:1. Introduction
- Permafrost-affected soils are not generally N-limited, but there are N hotspots of N availability with more open N cycling and increased potential for N losses in the form of inorganic N leaching and N2O emissions.
- N hotspots can be identified by certain soil characteristics and microbial traits: different N forms, microbial net N turnover rates, especially N mineralization, nitrification and denitrification, and abundance of key functional N cycling genes.
2. Regulation of N Availability by Microbial N Processes in Permafrost-Affected Soils
2.1. Levels and Traits of N Availability
2.2. Key Microbial N Processes Determining N Availability in Permafrost-Affected Soils
2.2.1. Nitrification
2.2.2. Denitrification
3. Hotspots of N Availability and Properties
3.1. Bare Organic Lowland Soils in Permafrost Peatland
3.1.1. Habitat, Soil Characteristics and Inorganic N
3.1.2. C and N Mineralization
3.1.3. Gaseous N Loss
Permafrost Peatland | Mineral Upland Soils in Thermokarst Landscapes | ||||
---|---|---|---|---|---|
Soil and Microbial Properties | Bare Surfaces * | Vegetated Surfaces * | Disturbed, Revegetated RTS ** | Undisturbed Fully Vegetated Site Next to RTS ** | |
Slump Floor (SF) | Thaw Mound (TM) | ||||
pH | 3.7 ± 0.5 [86,247] | 3.6 ± 0.3 [86,247] | 7.2 ± 1.5 [87,256] | 7.9 ± 0.0 [256] | 5.7 ± 0.3 [87] |
C/N | 22 ± 4 [86,247] | 51 ± 16 [86,247] | 15 ± 1 [87,256] | 13 ± 0 [256] | 38 ± 4 [87] |
WFPS (%) | 53 ± 25 [86,247] | 22 ± 7 [86,247] | 60 ± 11 [87,256] | 60 ± 3 [256] | 13 ± 6 [87] |
SOM (%) | 95 ± 1 [86,247] | 98 ± 0 [86,247] | 11 ± 4 [87,256] | 8 ± 0 [256] | 27 ± 3 [87] |
TN (%) | 2.4 ± 0.3 | 1.0 ± 0.3 | 0.30 ± 0.10 | 0.34 ± 0.01 | 0.29 ± 0.03 |
[86,247] | [86,247] | [87,256] | [256] | [87] | |
δ15N in bulk soil (‰) | n.d. | n.d. | 1.4 ± 0.5 [87,256] | 2.0 ± 0.1 [256] | 1.2 ± 0.3 [87] |
Ammonium (µg N g dw−1) | 60.1 ± 14.4 | 19.6 ± 5.7 | 1.4 ± 1.8 | 0.0 ± 0.0 | 9.0 ± 11.7 |
[86,202,205,216,247,255] | [86,202,205,216,247,255] | [87,256] | [256] | [87] | |
Nitrat (µg N g dw−1) | 116.8 ± 2.8 | 4.4 ± 7.7 | 0.7 ± 0.1 | 81.6 ± 24.3 | 0.0 ± 0.0 |
[86,202,205,216,247,255] | [86,202,205,216,247,255] | [87,256] | [256] | [87] | |
DIN/TN (%) | 1.1 ± 1.3 [86,247] | 0.3 ± 0.1 [86,247] | 0.1 ± 0.1 [87,256] | 2.4 [256] | 0.3 [87] |
Gross N mineralization | 16.8 ± 9.7 [86,202] | 9.0 ± 10.8 [86,202] | 15.1 ± 10.1 [87] | n.d. | b.d. |
(µg N g dw−1 d−1) | |||||
Net N mineralization | n.d. | n.d. | 4.0 ± 4.9 [87,256] | 1.4 ± 0.5 [256] | −20.9 ± 16.6 [87] |
(µg N g dw−1 d−1), p.a.s. 0.8 [59] | |||||
Gross nitrification | 8.4 ± 7.3 [120,202] | 0.2 ± 0.1 [202] | b.d. | n.d. | b.d. |
(µg N g dw−1 d−1), p.a.s. 6.6 [59] | |||||
Net nitrification | n.d. | n.d. | 1.6 ± 1.5 [87,256] | 1.4 ± 0.5 [256] | −6.0 ± 2.9 [87] |
(µg N g dw−1 d−1), p.a.s. −0.4 [59] | |||||
Net denitrification | 0.56 | <0.004 | 2.8 ± 1.8 [87] | n.d. | 0.01 ± 0.00 |
with (without acetylene) (µg N g dw−1 d−1) | (0.37) [205] | (b.d.) [205] | (0.3 ± 0.4) [87,256] | (0.20 ± 0.02) | (0.01 ± 0.00) |
[256] | [87] | ||||
Functional nitrification gene | |||||
AOA amoA (copies gdw−1) | 6.4 × 108 [120] | 8.0 × 106 [120] | 2.0 × 107 [87] | n.d. | 5.4 × 107 [87] |
AOB amoA (copies gdw−1) | b.d. | b.d. | 3.3 × 107 [87] | n.d. | 4.2 × 106 [87] |
Functional nitrification gene amoA (% of 16S rRNA) | |||||
n.d. | n.d. | 7 [87] | n.d. | 1 [87] | |
amoA (% of N genes) | n.d. | n.d. | 3.4 ± 1.0 [87] | n.d. | 0.5 ± 1.0 [87] |
Functional denitrification gene (% of 16S rRNA [205], N genes [87]) | |||||
narG | 7.6 ± 2.8 [205] | 0.04 ± 0.01 [205] | 42 ± 0.9 [87] | n.d. | 45 ± 9.3 [87] |
nirS + nirK | 0.34 ± 0.08 [205] | 0.88 ± 0.13 [205] | 29 ± 0.1 [87] | n.d. | 15 ± 0.6 [87] |
(nirS + nirK)/nosZ (%/%) | 0.20 × 103 [205] | 8.88 × 103 [205] | 2.4 ± 0.2 [87] | n.d. | 0.5 ± 0.1 [87] |
N2O fluxes | 1.98 ± 3.19 | 0.01 ± 0.03 | 1.64 ± 2.61 [87] | n.d. | −0.001 ± 0.018 [87] |
(mg N m−2 d−1) | [86,120,202,247,255] | [86,120,202,247,255] |
3.1.4. Microbial Based N Processes
3.2. Disturbed Mineral Upland Soils in Hillslope Thermokarst Landscapes
3.2.1. Habitat and Soil Characteristics
3.2.2. C and N Mineralization and Inorganic N
3.2.3. Gaseous N2O Loss and Based Microbial N Processes
3.2.4. Lateral N Loss
3.3. Bare Soils in the Transition between Terrestrial and Aquatic Ecosystems
3.4. Animal-Influenced Soils
3.5. Wildfire-Affected Soils
4. Hotspots of N Availability and Climate Change
4.1. Contribution of N Hotspots to Climate Change
4.2. Impact of Climate Change on N Hotspots
5. Conclusions and Perspectives
- Soil properties: Low C/N below a threshold of 25 [29,86,87,120,202,234,247,255,256], high δ15N of bulk soil [234,304], WFPS around 60–70% [82,86,87,120,202,217,247,256] and high DIN [28,29,86,87,120,188,189,202,208,210,213,214,234,247,255,256,292,304], sometimes expressed as higher DIN/DON ratio [256]. Nitrogen loss often correlates with dominance of nitrate over ammonium [29,87,213,216,217,247,255,256], but at some sites a higher ammonium content was found in association with higher N2O emission [86,188,189,248,306]. Therefore, the total inorganic N content would be a better indicator for N loss.
- Microbial process rates measured in situ or in laboratory incubations correlated with N loss and were therefore appropriate traits of high N availability. They were gross [202,216] and net mineralization, the sum of ammonification and nitrification [87,304], gross [111,120,202] and net nitrification [29,69,87,119,188,304,307] and denitrification [189,205,234,254,256]. Since gross N turnover rates are also indicative of the total amount of circulating N and theses rates were higher than currently expected in this ecosystem [59], we propose to use net rates as an indicator of N limitation status instead. Net rates could provide a better indication of how much N might be lost from the tight N cycling system of permafrost-affected soils. However, net rates estimated using laboratory incubation techniques are highly dependent on conditions such as temperature and have inherent biases related to functional groups, so they do not characterize the contribution of, e.g., nitrifying organisms in the natural habitat [379]. Recently, however, in situ N2O flux rates from an N hotspot were shown to be highly correlated with anaerobic N2O production in laboratory incubation tests, as well as with net mineralization and net nitrification [87], so laboratory tests could be a good tool for predicting field fluxes.
- The abundance of functional genes or the detection of known 16S rRNA gene sequences of nitrifiers [119,120,188], denitrifiers [189,218], or both [86] have been correlated with high N2O losses in N hotspots. For nitrifiers, especially ammonia-oxidizing bacteria (AOB) and archaea (AOA), the gene amoA was mostly applied. However, gene AOA amoA abundance also dominated in permafrost-affected soils [118,120,147,182], but generally did not correlate with nitrification activity and N2O production rates. The reasons are that AOA do not exclusively use ammonia as substrate and that AOA produce N2O with about 30 times lower yields [129]. Therefore, it will likely be useful to distinguish between AOA and AOB amoA when using as traits for N2O production in the future. To predict N2O production by denitrifiers, high levels of their functional genes, mainly nirS + nirK genes of nitrite reductase, low levels of the gene nosZ (N2O reductase), or a high ratio of (nirS + nirK)/nosZ, were found in N hotspots in correlation with high N2O emission [205,218] and could therefore be a suitable microbial trait for N losses. In addition, metatranscriptomic analysis, which detects actively produced transcripts, could be another good tool to detect active microbial N cycling and N losses. This detection method has recently shown a correlation between denitrification activity and N2O production in permafrost-affected soils [136].
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Fiencke, C.; Marushchak, M.E.; Sanders, T.; Wegner, R.; Beer, C. Microbiogeochemical Traits to Identify Nitrogen Hotspots in Permafrost Regions. Nitrogen 2022, 3, 458-501. https://doi.org/10.3390/nitrogen3030031
Fiencke C, Marushchak ME, Sanders T, Wegner R, Beer C. Microbiogeochemical Traits to Identify Nitrogen Hotspots in Permafrost Regions. Nitrogen. 2022; 3(3):458-501. https://doi.org/10.3390/nitrogen3030031
Chicago/Turabian StyleFiencke, Claudia, Maija E. Marushchak, Tina Sanders, Rica Wegner, and Christian Beer. 2022. "Microbiogeochemical Traits to Identify Nitrogen Hotspots in Permafrost Regions" Nitrogen 3, no. 3: 458-501. https://doi.org/10.3390/nitrogen3030031
APA StyleFiencke, C., Marushchak, M. E., Sanders, T., Wegner, R., & Beer, C. (2022). Microbiogeochemical Traits to Identify Nitrogen Hotspots in Permafrost Regions. Nitrogen, 3(3), 458-501. https://doi.org/10.3390/nitrogen3030031