the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Aug 2024
Remote carbon cycle changes are overlooked impacts of land-cover and land management changes
Abstract. Land-cover and land management changes (LCLMCs) have a substantial impact on the global carbon budget and, consequently, global climate. However, LCLMCs also influence climate by altering the surface energy balance, namely biogeophysical (BGP) effects. BGP effects act locally, but also nonlocally through advection or atmospheric circulation changes. Previous studies have shown potentially substantial nonlocal BGP effects on temperature and precipitation. Given that the terrestrial carbon cycle strongly depends on climate conditions, this raises the question of whether LCLMCs can trigger remote carbon cycle changes – a currently overlooked potentially large climate and ecosystem impact. To assess these nonlocal biogeochemical (BGC) effects, we analyze sensitivity simulations for three selected types of hypothetical large-scale LCLMCs: global cropland expansion, global cropland expansion with irrigation, and global afforestation, which were performed by three state-of-the-art Earth system models. We separate the nonlocal BGC effect using a checkerboard-like LCLMC perturbation that has previously only been applied to BGP effects. We show that nonlocal BGC effects on vegetation and soil carbon pools persistently accumulate, exceeding natural fluctuations and typically becoming detectable within the first 40 years after LCLMCs. By the end of our 160-year simulation period, the global total terrestrial carbon stock differs by 1 to 37 GtC, with strong changes over the densely forested Amazon region (0.2 to 7 GtC) and Congo region (0.3 to 15 GtC), depending on models and scenarios. For the irrigation scenario, the nonlocal BGC effects are comparable to the total BGC effects. Our results reveal that the nonlocal BGC effects could be substantial and call for these effects to be considered for accurate impact assessment and sound policymaking. This becomes even more relevant when LCLMCs are expected to play a pivotal role in achieving the Paris Agreement’s goal of limiting global warming below 1.5 °C above pre-industrial levels.
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Status: open (until 23 Sep 2024)
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RC1: 'Comment on egusphere-2024-2387', Anonymous Referee #1, 27 Aug 2024
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The following is my review of the paper entitled ‘Remote carbon cycle changes are overlooked impacts of land-cover and land management changes’ by Guo et al., submitted to Earth Science Dynamics. In this paper, the authors have studied the local and non-local impacts of land cover change and its management on climate variability. The warming effects are classified into biogeophysical (BGP) and biogeochemical (BGC) categories, and multiple Earth system models are used to simulate these changes for afforestation and agricultural expansion with and without irrigation. The BGC impacts are found to be significant and should be considered in impact assessment and relevant policymaking. For the irrigated cropland expansion scenario, the cumulative impacts of local and non-local BGC effects will become comparable in the future. Overall, this work is relevant to climate research, has novelty and has been conducted extensively. However, the article is written in a manner that is hard to understand, and it requires several other improvements, as I listed below.
Specific comments:
- This paper is very complicated to comprehend, primarily due to its structure and writing style. The descriptions of experiments and corresponding model simulations are tough to understand. There are a lot of differences among the different model experiments and their simulations. There are multiple variables considered and their interrelations. Consequently, there are multiple figures (seventeen, including the ones in the appendices, and each with multiple subplots!). However, these are not explained in sufficient detail. This makes the results inconclusive. Most of the interpretations are not clear and some of those are speculative in nature.
- Perhaps it will be helpful for the readers to categorize the biogeophysical and biogeochemical effects into local and nonlocal categories and represent this information in a table.
- How the effects are separated into local and non-local is not objectively defined. Did they use any preset definition of the ‘area of influence’ or did they use a specific number of neighboring points (pixels) for such classifications?
- Lines 59-61: I do not totally understand this statement. Changing a forest to grassland will reduce its carbon sequestration, which will increase atmospheric warming. This is a global effect and biogeochemical in nature. On the other hand, an increase in albedo will impart a cooling that is local and biogeophysical in nature.
- Lines 130-135: The second advantage of not considering the plausible realizations in the modeling experiments is not clear.
- CROP scenario in Table 1: So, here, basically, two land use types are considered: cropland and bare soil, right? And both these occupy 50% of each of the land grid cells? Are different biophysical and biogeochemical parameters used for the different crop types, such as albedo, rooting depth, etc.?
- IRR scenario in Table 1: Since all the croplands were irrigated, did the authors check the hydrological budget and ensure its closure globally? Also, what kind of irrigation was considered, fed with surface or groundwater, drip or canal, etc.? These details are required.
- Lines 160-162: See my earlier comment on the water budget.
- Section 2.2: The recipe used here to differentiate between the local and non-local effects is not clear. Can the authors show a flowchart summarizing these?
- Lines 236-241: Why are changes in surface roughness due to land cover change and its impact on aerodynamic conductance not considered?
- Figure 2: Please improve the description of different components of the terrestrial carbon cycle simulated by different models. In the present format, it is utterly confusing for the readers. For example, what about the blue dashed line? To interpret this the reader has to read the caption. Why then some other lines are described in the figure itself? Use a uniform and detailed description and present those in a way straightforward to understand.
- Figure 3: How are the boxes selected in panel (a) for calculating the regional averages? The boxes over northern America and Australia include oceans as well, which should not be counted in the terrestrial carbon cycle. Why don’t the authors use appropriate shapefiles to select and crop the regions of their interest?
- Can the authors show spatial trends of different carbon pools for different experiments and models over the simulation period for the aforementioned regions?
- Consistent scales should be used across the subplots in all the figures. For example, the scales on the y-axis are different in the subplots of Figure 2. Similarly, the x-axis scales are different in panels (d), (h) and (l) in Figure 3. This makes the intercomparison difficult.
- Lines 379-383: Shouldn't the ToE for the forested regions should be slower than croplands and grasslands, since the total biomass content is significantly higher in the former land use type?
- Figure C1: What do the panels j and k stand for? This should be described in the figure caption.
- Several references cited in the text are missing from the bibliography, such as Arora et al.
Technical corrections:
- Line 165: "are shown" instead of "is shown".
- Figure 5: CESM is marked blue; however, in the caption, it is written as red.
- Lines 467-483: This is a big paragraph. Consider breaking it into two or more.
Citation: https://doi.org/10.5194/egusphere-2024-2387-RC1
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