the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 May 2024
Quantifying the impacts of wildfires on soil thermal, hydrological and carbon dynamics in northern Eurasia from 2003 to 2016
Abstract. We use a process-based biogeochemistry model to simulate the fire impacts on soil thermal and hydrological dynamics and carbon budget of forest ecosystems in Northern Eurasia during 2003–2016 based on satellite-derived burn severity data. We find that fire severity generally increases in this region during the study period. Simulations indicate that fires increase soil temperature by 0.2–0.5 °C through removing the ground moss and surface soil organic matter, especially in Asian part of the region. Fires also increase water runoff by about 131 million m3 yr-1 through reducing post-fire evapotranspiration, leading to a higher regional river discharge. Fires remove 1.7 Pg C of ecosystem carbon through combustion emissions during this period and reduce net ecosystem production from 106.4 to 66.1 Tg C yr-1. Fires lead the forest ecosystems to lose 2.3 Pg C, shifting the forests from a carbon sink to a source in this period. Our study highlights the importance of wildfires in affecting soil thermal and hydrological and carbon dynamics in boreal forests.
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RC1: 'Comment on egusphere-2024-1324', Anonymous Referee #1, 11 Jul 2024
In this manuscript, the authors force the TEM model with burned area and severity derived from a neat satellite data analysis. They then do another run with no fire and compare, across Eurasian boreal forests for 2003-2016, the two runs’ soil temperature, hydrology, and carbon. In this way, they quantify fire’s contribution to energy, water, and carbon fluxes in this biome.
The manuscript is well-organized and well-written. The analyses are sufficient to support most of the conclusions, although I have one additional suggestion. In all, I recommend this paper for acceptance pending minor revisions.
Main comments
- How much of a reduction in litter post-fire is there? Fire burns some portion of litter, of course, and the reduction in LAI means there’s less litter being generated. But is any of that lost LAI dropped to litter? It might be helpful to see a time series of net litter flux in burned areas before and after fire.
- Does litter have an insulating effect like moss does?
- I was surprised to see negative dNBR values. I see now that’s mathematically possible, but how should a reader interpret such values?
- Any ideas why fire might decrease soil temperature in some places?
Minor comments/corrections
- P3L19: Citation needed for Landsat data?
- P7L1-2 (Fig. 2 caption): Is gray nonforest/not simulated?
- P11L21: The “previous estimates” referred to are the Pan-Arctic ones, yes? This could be mentioned in this sentence for clarity.
- P12L10: I think this should be equation 4, not 2.
- P13L8-9: Worth pointing out that this limitation doesn’t apply to your per-watershed analysis (Table 2).
Citation: https://doi.org/10.5194/egusphere-2024-1324-RC1 - AC1: 'Reply on RC1', Yiming Xu, 30 Sep 2024
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RC2: 'Comment on egusphere-2024-1324', Anonymous Referee #2, 15 Sep 2024
Review of “Quantifying the impacts of wildfires on soil thermal, hydrological and carbon dynamics in northern Eurasia from 2003 to 2016”
by Yiming Xu et al.
Submitted to Biogeosciences (egusphere-2024-1324)
The authors use the Terrestrial Ecosystem Model along with prescribed remote sensing data of fire occurrence and burn severity to examine the effects of fire on the ecosystems of boreal Eurasia. They report changes in soil temperature, carbon fluxes (both combustion and ecosystem productivity) and water fluxes. The subject matter is worthy of publication in Biogeosciences and increasing our understanding of the impacts of fire in high latitude ecosystems – particularly with respect to changing climate and fire regimes – is important. The results are generally well-presented and the manuscript is compact (although perhaps somewhat too compact, see below). The methods (in general terms) are appropriate for the goals of the study.
However, the manuscript has a three major shortcomings.
-
The authors offer absolutely no evaluation of model performance for the study region. As the authors state, the parameterisation was developed for North America not Eurasia. The two regions have different ecologies – including different fire regimes and different species with different fire response strategies (i.e. embracer vs resistor strategies) (Rogers et al. 2015). The quoted evaluation for North America was fairly light – three sites with large error bars. The original site level evaluation of Zhuang et al. (2002) is good but only goes so far because 1. it only covers black spruce sites (a species not found in Eurasia) and 2. doesn’t include the 20+ years of satellite data now available. Firstly, are there site measurement from Eurasia that could be used? But secondly, failing that, there are now a plethora of products that can be used to assess the model performance over the current study region. MODIS GPP/NPP and GOSIF GPP would be amongst the obvious choices, but also (depending on exactly what is prescribed as input to the model and what is calculated) LAI, treecover, biomass and FAPAR could be used. Also soil moisture products as the authors quote soil moisture results, and GLEAM could be used for hydrological variables (although it is a modelled product that might better be used for context, see point 2. below). There might be some reasons why the benchmarking I suggest is inappropriate, or perhaps the authors can explain why the parameterisation for the North America is suitable for Eurasia, but they must address this.
-
The results badly lack context in terms of numerical magnitudes. Some of this could be address by including observed values (see above) to give context, but in many cases just a little bit of extra information (such as baseline values without fire) is needed to make the tables and figures actually informative. For example:
-
Figure 5. Each of these maps should be presented as both the absolute difference and relative change. For panels a) and b) it is important to know if these changes actually amount to much in relative terms (I feel that the evapotranspiration changes are likely negligible, even though the result is quoted in the abstract). For panel c), the LAI changes look considerable, but it would be important to know what the baseline was.
-
Table 2 – these numbers differ by three orders of magnitude! Of course different basins have different sizes so this is understandable, but please give the simulated baseline (and ideally gauging station data if available) so that we can assess these changes in context.
-
Table 3 – there is no reason that the authors can’t subset their estimates to the regions of “Russia”, “Eurasia”, “Pan-arctic” and “Siberia” to better put their results in context of the others. There are also global fire emissions products – GFAS, GFED etc – that can be easily calculated for the region and included here.
-
The abstract result of a reduction of 131 million m3 yr-1, how much is that as a proportion of the current run-off?
-
-
Much methodological detail is missing. Details of how the plant functional types were derived and prescribed are needed. Also details of how fire was prescribed (presumably applied to a fraction of a gridcell only?) are missing. How are photosynthesis and fapar calculated? And respiration? How is vegetation represented - average individual or cohorts or something more abstract? The description of the processing of the GFA data is admirably complete (full marks there), but at least a passing description of the other aspects of the model are required. It would is also important to know how the parameters (of which there are quite number, at least p1, p2, a1, b1 and gamma) were derived and what is there values. There is a small attempt to examine parameter uncertainty by changing values by 10% but we don’t have any idea what the uncertainty on the paramaters actually is and only p1, p2, p3, and p4 are tested. What about a1, b1 and gamma? And possible other parameters that are not introduced in the current text? And the p3 is quoted as being the major source of uncertainty – but what about the amount of biomass that is present to burn? That will be a huge factor, but we have no idea how that was calculated (new mind how much below ground and how much above ground) and what the uncertainty on that is. Without further information, I would guess this is the largest source of uncertainty in the study.
At the end of the day, the lack of evaluation is the biggest problem here. Without it, the results given here are just model output about which it is hard to have any confidence. There are a plethora of datasets out there that can be used to evaluate the model or at least give context. The lack of methodological details and context also inhibit confidence. These three points also combine to give a lack of clarity on what is the real novelty of the results. Global models (fire-enabled DGVMs for example) could also be used to produce these results. These models would likely not show particularly good model skill, so using a regional model is definitely a good idea. But without model evaluation and greater methodological clarity, one can’t be sure that the application of TEM (uncalibrated for the study region) is really an improvement. On account of the these three points, I am suggesting major revisions. If these points are comprehensively addressed I am willing to review the manuscript again as I believe it shows definite potential.
Rogers, B., Soja, A., Goulden, M. et al. Influence of tree species on continental differences in boreal fires and climate feedbacks. Nature Geosci 8, 228–234 (2015). https://doi.org/10.1038/ngeo2352Zhuang, Q., Mcguire, A. D., O'Neill, K. P., Harden, J. W., Romanovsky, V. E., and Yarie, J.: Modeling soil thermal and carbon dynamics of a fire chronosequence in interior alaska, J. Geophys. Res.: Atmos., 107(D1), 2002.
Zhuang, Q., Mcguire, A. D., O'Neill, K. P., Harden, J. W., Romanovsky, V. E., and Yarie, J.: Modeling soil thermal and carbon dynamics of a fire chronosequence in interior alaska, J. Geophys. Res.: Atmos., 107(D1), 2002.
Citation: https://doi.org/10.5194/egusphere-2024-1324-RC2 - AC2: 'Reply on RC2', Yiming Xu, 30 Sep 2024
-
Status: closed
-
RC1: 'Comment on egusphere-2024-1324', Anonymous Referee #1, 11 Jul 2024
In this manuscript, the authors force the TEM model with burned area and severity derived from a neat satellite data analysis. They then do another run with no fire and compare, across Eurasian boreal forests for 2003-2016, the two runs’ soil temperature, hydrology, and carbon. In this way, they quantify fire’s contribution to energy, water, and carbon fluxes in this biome.
The manuscript is well-organized and well-written. The analyses are sufficient to support most of the conclusions, although I have one additional suggestion. In all, I recommend this paper for acceptance pending minor revisions.
Main comments
- How much of a reduction in litter post-fire is there? Fire burns some portion of litter, of course, and the reduction in LAI means there’s less litter being generated. But is any of that lost LAI dropped to litter? It might be helpful to see a time series of net litter flux in burned areas before and after fire.
- Does litter have an insulating effect like moss does?
- I was surprised to see negative dNBR values. I see now that’s mathematically possible, but how should a reader interpret such values?
- Any ideas why fire might decrease soil temperature in some places?
Minor comments/corrections
- P3L19: Citation needed for Landsat data?
- P7L1-2 (Fig. 2 caption): Is gray nonforest/not simulated?
- P11L21: The “previous estimates” referred to are the Pan-Arctic ones, yes? This could be mentioned in this sentence for clarity.
- P12L10: I think this should be equation 4, not 2.
- P13L8-9: Worth pointing out that this limitation doesn’t apply to your per-watershed analysis (Table 2).
Citation: https://doi.org/10.5194/egusphere-2024-1324-RC1 - AC1: 'Reply on RC1', Yiming Xu, 30 Sep 2024
-
RC2: 'Comment on egusphere-2024-1324', Anonymous Referee #2, 15 Sep 2024
Review of “Quantifying the impacts of wildfires on soil thermal, hydrological and carbon dynamics in northern Eurasia from 2003 to 2016”
by Yiming Xu et al.
Submitted to Biogeosciences (egusphere-2024-1324)
The authors use the Terrestrial Ecosystem Model along with prescribed remote sensing data of fire occurrence and burn severity to examine the effects of fire on the ecosystems of boreal Eurasia. They report changes in soil temperature, carbon fluxes (both combustion and ecosystem productivity) and water fluxes. The subject matter is worthy of publication in Biogeosciences and increasing our understanding of the impacts of fire in high latitude ecosystems – particularly with respect to changing climate and fire regimes – is important. The results are generally well-presented and the manuscript is compact (although perhaps somewhat too compact, see below). The methods (in general terms) are appropriate for the goals of the study.
However, the manuscript has a three major shortcomings.
-
The authors offer absolutely no evaluation of model performance for the study region. As the authors state, the parameterisation was developed for North America not Eurasia. The two regions have different ecologies – including different fire regimes and different species with different fire response strategies (i.e. embracer vs resistor strategies) (Rogers et al. 2015). The quoted evaluation for North America was fairly light – three sites with large error bars. The original site level evaluation of Zhuang et al. (2002) is good but only goes so far because 1. it only covers black spruce sites (a species not found in Eurasia) and 2. doesn’t include the 20+ years of satellite data now available. Firstly, are there site measurement from Eurasia that could be used? But secondly, failing that, there are now a plethora of products that can be used to assess the model performance over the current study region. MODIS GPP/NPP and GOSIF GPP would be amongst the obvious choices, but also (depending on exactly what is prescribed as input to the model and what is calculated) LAI, treecover, biomass and FAPAR could be used. Also soil moisture products as the authors quote soil moisture results, and GLEAM could be used for hydrological variables (although it is a modelled product that might better be used for context, see point 2. below). There might be some reasons why the benchmarking I suggest is inappropriate, or perhaps the authors can explain why the parameterisation for the North America is suitable for Eurasia, but they must address this.
-
The results badly lack context in terms of numerical magnitudes. Some of this could be address by including observed values (see above) to give context, but in many cases just a little bit of extra information (such as baseline values without fire) is needed to make the tables and figures actually informative. For example:
-
Figure 5. Each of these maps should be presented as both the absolute difference and relative change. For panels a) and b) it is important to know if these changes actually amount to much in relative terms (I feel that the evapotranspiration changes are likely negligible, even though the result is quoted in the abstract). For panel c), the LAI changes look considerable, but it would be important to know what the baseline was.
-
Table 2 – these numbers differ by three orders of magnitude! Of course different basins have different sizes so this is understandable, but please give the simulated baseline (and ideally gauging station data if available) so that we can assess these changes in context.
-
Table 3 – there is no reason that the authors can’t subset their estimates to the regions of “Russia”, “Eurasia”, “Pan-arctic” and “Siberia” to better put their results in context of the others. There are also global fire emissions products – GFAS, GFED etc – that can be easily calculated for the region and included here.
-
The abstract result of a reduction of 131 million m3 yr-1, how much is that as a proportion of the current run-off?
-
-
Much methodological detail is missing. Details of how the plant functional types were derived and prescribed are needed. Also details of how fire was prescribed (presumably applied to a fraction of a gridcell only?) are missing. How are photosynthesis and fapar calculated? And respiration? How is vegetation represented - average individual or cohorts or something more abstract? The description of the processing of the GFA data is admirably complete (full marks there), but at least a passing description of the other aspects of the model are required. It would is also important to know how the parameters (of which there are quite number, at least p1, p2, a1, b1 and gamma) were derived and what is there values. There is a small attempt to examine parameter uncertainty by changing values by 10% but we don’t have any idea what the uncertainty on the paramaters actually is and only p1, p2, p3, and p4 are tested. What about a1, b1 and gamma? And possible other parameters that are not introduced in the current text? And the p3 is quoted as being the major source of uncertainty – but what about the amount of biomass that is present to burn? That will be a huge factor, but we have no idea how that was calculated (new mind how much below ground and how much above ground) and what the uncertainty on that is. Without further information, I would guess this is the largest source of uncertainty in the study.
At the end of the day, the lack of evaluation is the biggest problem here. Without it, the results given here are just model output about which it is hard to have any confidence. There are a plethora of datasets out there that can be used to evaluate the model or at least give context. The lack of methodological details and context also inhibit confidence. These three points also combine to give a lack of clarity on what is the real novelty of the results. Global models (fire-enabled DGVMs for example) could also be used to produce these results. These models would likely not show particularly good model skill, so using a regional model is definitely a good idea. But without model evaluation and greater methodological clarity, one can’t be sure that the application of TEM (uncalibrated for the study region) is really an improvement. On account of the these three points, I am suggesting major revisions. If these points are comprehensively addressed I am willing to review the manuscript again as I believe it shows definite potential.
Rogers, B., Soja, A., Goulden, M. et al. Influence of tree species on continental differences in boreal fires and climate feedbacks. Nature Geosci 8, 228–234 (2015). https://doi.org/10.1038/ngeo2352Zhuang, Q., Mcguire, A. D., O'Neill, K. P., Harden, J. W., Romanovsky, V. E., and Yarie, J.: Modeling soil thermal and carbon dynamics of a fire chronosequence in interior alaska, J. Geophys. Res.: Atmos., 107(D1), 2002.
Zhuang, Q., Mcguire, A. D., O'Neill, K. P., Harden, J. W., Romanovsky, V. E., and Yarie, J.: Modeling soil thermal and carbon dynamics of a fire chronosequence in interior alaska, J. Geophys. Res.: Atmos., 107(D1), 2002.
Citation: https://doi.org/10.5194/egusphere-2024-1324-RC2 - AC2: 'Reply on RC2', Yiming Xu, 30 Sep 2024
-
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Quantifying the impacts of wildfires on soil thermal, hydrological and carbon dynamics in northern Eurasia from 2003 to 2016 Qianlai Zhuang and Yiming Xu https://doi.org/10.4231/ZJM7-A207
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