the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Soil respiration across a variety of tree-covered urban green spaces in Helsinki, Finland
Abstract. As an increasing share of the human population is being clustered in cities, urban areas have swiftly become the epicentres of anthropogenic carbon (C) emissions. Understanding different parts of the biogenic C cycle in urban ecosystems is needed in order to assess the potential of enhancing their C stocks as a cost-efficient means to balance the C emissions and mitigate climate change. Here, we conducted a field measurement campaign over three consecutive growing seasons to examine soil respiration carbon dioxide (CO2) fluxes and soil organic carbon (SOC) stocks at four measurement sites in Helsinki representing different types of tree-covered urban green space commonly found in northern European cities. We expected to find variation in the main drivers of soil respiration – soil temperature, soil moisture, and SOC – as a result of the heterogeneity of urban landscape, and that this variation would be reflected in the measured soil respiration rates. In the end, we could see fairly constant statistically significant differences between the sites in terms of soil temperature but only sporadic and seemingly momentary differences in soil moisture and soil respiration. There were also statistically significant differences in SOC stocks: the highest SOC stock was found in inactively managed deciduous urban forest and the lowest under managed streetside lawn with common linden trees. We studied the impacts of the urban heat island (UHI) effect and irrigation on heterotrophic soil respiration with process-based model simulations, and found that the variation created by the UHI is relatively minor compared to the increase associated with active irrigation, especially during dry summers. We conclude that, within our study area, the observed variation in soil temperature alone was not enough to cause variation in soil respiration rates between the studied green space types, perhaps because the soil moisture conditions were uniform. Thus, irrigation could potentially be a key factor in altering the soil respiration dynamics in urban green space both within the urban area and in comparison to non-urban ecosystems.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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Supplement
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(4910 KB) - Metadata XML
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Supplement
(151 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-3031', Anonymous Referee #1, 11 Feb 2024
General comments
The authors present results from a temporally extensive dataset providing insights into soil respiration dynamics in urban green spaces. The objectives were to distinguish differences in soil respiration rates measured in different types of tree-covered urban greenspace as well as assessing the impact of the UHI effect and increased irrigation on soil respiration. Results suggest that despite differences in sites, management, tree cover, SOC and soil temperature there were no distinct differences in soil respiration - possibly due to similar soil moisture contents across the sites. Further, model results suggest that while increased irrigation may result in an up to 50% increase in heterotrophic soil respiration an increase in air temperature related to the UHI effect only has a small impact on urban forest and park sites.
Overall, the paper is well written with clear objectives and conclusions supported by the results. The use of an ecosystem model to understand UHI effects and the impact of irrigation on soil respiration seems to be an interesting approach and encourages further studies to simulate the urban carbon cycle for different future scenarios. However, there is a need to add further information about the ecosystem model as outlined below.
Specific comments
Re ecosystem modelling - It may help having a paragraph in the introduction introducing the model, what it does, how it is used and what the model inputs/outputs are and if it has been applied for similar applications as in this paper. It also seems there are a lot of assumptions being made about model inputs and it is not always clear how these vary across the different sites and whether these introduce any uncertainties into the model results.
P5 L126 Measurements were undertaken between 8 AM and 4 PM – did you notice any diurnal variations depending on the time of day the measurements were taken? And if so, how did this affect results?
P5 L129 how were measurement points selected within each site?
2.7 Ecosystem modelling
As mentioned above, this section is not very clear. It may help summarising the general inputs (met data, vegetation data, soil characteristics) and outputs of the model and how these were determined for the forest and park site.
P9 L249: How was root depth determined? Is this a guess?
P9 L256: the loss rates were modified using the temperature and precipitation data from the FMI Kumpala weather station? How was the size of the litter elements determined?
3.4 Modelled RH dynamics – this seems more like a model validation? It would help having a sentence to introduce the purpose of this section (ie comparing temporal variations of modelled reference to observations?) (ie Figure 5 excluding modelled irrigation)
3.5 This section then describes the results from the UHI and irrigation simulations (Figure 6).
P16 L340: Move sentence about impact of the UHI to P18 L411.
P16 L361: SOC stocks were similar to those measured other top layers (0 – 30 cm) but on the lower end compared to studies that measured SOC stocks to 100 cm.
P18 L416: I guess this is not as surprising given the above statement (L398) and previous studies indicating that soil moisture is the main factor controlling urban Rs?
Table 4 – Consider adding your results too for direct comparison.
Technical corrections
Figure 5/6 – the manual measurement points and facets are hard to see in Figure 5 and 6 please use a darker shade or colours to distinguish these.
Citation: https://doi.org/10.5194/egusphere-2023-3031-RC1 - AC1: 'Reply on RC1', Esko Karvinen, 05 Apr 2024
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RC2: 'Comment on egusphere-2023-3031', Anonymous Referee #2, 14 Mar 2024
Karvinen et al. conducted a field measurement over three consecutive growing seasons to examine soil respiration CO2 fluxes and SOC stocks at four measurement sites in Helsinki. The authors conclude that the observed variation in soil temperature alone was not enough to cause variation in soil respiration rates between the studied green space types, perhaps because the soil moisture conditions were uniform, therefore, irrigation could potentially be a key factor in altering the soil respiration dynamics. The manuscript is well-prepared and easy to follow, and the topic is interesting and important.
The mechanisms leading to the varying soil respiration are very complex, for example, in addition to soil temperature and moisture, soil pH and P, K, SOC, and SON are also important and these soil factors change across different seasons. Rather than total SOC, DOC (dissolved organic carbon) could be more closely related to soil respiration. Besides, the microbial community is key to soil respiration, however, it is not considered in this study. So, I recommend more analysis related to the variation in soil respiration.
Citation: https://doi.org/10.5194/egusphere-2023-3031-RC2 - AC2: 'Reply on RC2', Esko Karvinen, 05 Apr 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-3031', Anonymous Referee #1, 11 Feb 2024
General comments
The authors present results from a temporally extensive dataset providing insights into soil respiration dynamics in urban green spaces. The objectives were to distinguish differences in soil respiration rates measured in different types of tree-covered urban greenspace as well as assessing the impact of the UHI effect and increased irrigation on soil respiration. Results suggest that despite differences in sites, management, tree cover, SOC and soil temperature there were no distinct differences in soil respiration - possibly due to similar soil moisture contents across the sites. Further, model results suggest that while increased irrigation may result in an up to 50% increase in heterotrophic soil respiration an increase in air temperature related to the UHI effect only has a small impact on urban forest and park sites.
Overall, the paper is well written with clear objectives and conclusions supported by the results. The use of an ecosystem model to understand UHI effects and the impact of irrigation on soil respiration seems to be an interesting approach and encourages further studies to simulate the urban carbon cycle for different future scenarios. However, there is a need to add further information about the ecosystem model as outlined below.
Specific comments
Re ecosystem modelling - It may help having a paragraph in the introduction introducing the model, what it does, how it is used and what the model inputs/outputs are and if it has been applied for similar applications as in this paper. It also seems there are a lot of assumptions being made about model inputs and it is not always clear how these vary across the different sites and whether these introduce any uncertainties into the model results.
P5 L126 Measurements were undertaken between 8 AM and 4 PM – did you notice any diurnal variations depending on the time of day the measurements were taken? And if so, how did this affect results?
P5 L129 how were measurement points selected within each site?
2.7 Ecosystem modelling
As mentioned above, this section is not very clear. It may help summarising the general inputs (met data, vegetation data, soil characteristics) and outputs of the model and how these were determined for the forest and park site.
P9 L249: How was root depth determined? Is this a guess?
P9 L256: the loss rates were modified using the temperature and precipitation data from the FMI Kumpala weather station? How was the size of the litter elements determined?
3.4 Modelled RH dynamics – this seems more like a model validation? It would help having a sentence to introduce the purpose of this section (ie comparing temporal variations of modelled reference to observations?) (ie Figure 5 excluding modelled irrigation)
3.5 This section then describes the results from the UHI and irrigation simulations (Figure 6).
P16 L340: Move sentence about impact of the UHI to P18 L411.
P16 L361: SOC stocks were similar to those measured other top layers (0 – 30 cm) but on the lower end compared to studies that measured SOC stocks to 100 cm.
P18 L416: I guess this is not as surprising given the above statement (L398) and previous studies indicating that soil moisture is the main factor controlling urban Rs?
Table 4 – Consider adding your results too for direct comparison.
Technical corrections
Figure 5/6 – the manual measurement points and facets are hard to see in Figure 5 and 6 please use a darker shade or colours to distinguish these.
Citation: https://doi.org/10.5194/egusphere-2023-3031-RC1 - AC1: 'Reply on RC1', Esko Karvinen, 05 Apr 2024
-
RC2: 'Comment on egusphere-2023-3031', Anonymous Referee #2, 14 Mar 2024
Karvinen et al. conducted a field measurement over three consecutive growing seasons to examine soil respiration CO2 fluxes and SOC stocks at four measurement sites in Helsinki. The authors conclude that the observed variation in soil temperature alone was not enough to cause variation in soil respiration rates between the studied green space types, perhaps because the soil moisture conditions were uniform, therefore, irrigation could potentially be a key factor in altering the soil respiration dynamics. The manuscript is well-prepared and easy to follow, and the topic is interesting and important.
The mechanisms leading to the varying soil respiration are very complex, for example, in addition to soil temperature and moisture, soil pH and P, K, SOC, and SON are also important and these soil factors change across different seasons. Rather than total SOC, DOC (dissolved organic carbon) could be more closely related to soil respiration. Besides, the microbial community is key to soil respiration, however, it is not considered in this study. So, I recommend more analysis related to the variation in soil respiration.
Citation: https://doi.org/10.5194/egusphere-2023-3031-RC2 - AC2: 'Reply on RC2', Esko Karvinen, 05 Apr 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
Soil respiration, soil carbon, soil temperature, and soil moisture measured in urban green spaces in Helsinki during 2020-2022 Esko Karvinen http://hdl.handle.net/11304/9961c5ae-e967-4033-9bfa-3f734307def0
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Leif Backman
Leena Järvi
Liisa Kulmala
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(4910 KB) - Metadata XML
-
Supplement
(151 KB) - BibTeX
- EndNote
- Final revised paper