the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Dec 2025
Climate extremes limiting the growth of East Asian mangroves for future nature-based solutions
Abstract. Mangroves represent distinctive coastal ecosystems that offer ecological benefits, notably through their high carbon sequestration rates. However, their resilience to extreme climate events remains uncertain. Here, we investigate the response of mangroves in East Asia to climate variability by employing the remote-sensing derived normalized difference vegetation index as a proxy for mangrove health. We found East Asian mangrove growth has positive relations with temperature and solar radiation, particularly in cumulative anomalies on seasonal time scales. These findings are extrapolated to future projections by the Earth system modelling to explore not only existing mangroves but also potential habitats. While shifts in wintertime isotherms indicate northward expansion of mangroves under global warming, low solar radiation events associated with aerosol emissions in East Asia could remain as a limiting factor for their growth. This study underscores the importance of climate extremes in practical planning for future mangrove conservation, restoration, and migration, which are considered effective nature-based climate solutions.
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Status: open (until 16 Jan 2026)
- RC1: 'Comment on egusphere-2025-5805', Anonymous Referee #1, 13 Jan 2026 reply
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Review of Manuscript egusphere-2025-5805
The authors provide an important and relevant analysis regarding the climatic conditions, particularly temperature and solar radiation, that influence mangrove growth in East Asia. The manuscript utilizes a set of excellent methodologies consisting of remote sensing data (NDVI), climate data from the ERA5 model, and projected data from CMIP6. The authors' attention to not only examine the current dynamics but also project future habitat suitability based on the selected climatic conditions in the regions divided by latitudinal zones complements the significance of their manuscript in the realm of mangrove ecologies and climate solutions. The manuscript is well-organized with proper written content. The techniques are excellent, and the conclusion has been well-formulated based on the results. There are some points that need to be clarified with adequate discussions in order to increase the significance of the MS. The comments are mentioned below for the authors' consideration in publishing the MS.
GENERAL COMMENTS
The manuscript presents a strong case regarding the explanatory value of solar radiation, which has been, to a certain extent, underestimated in mangrove-related studies. This is certainly one of the main strong points of this manuscript. Nevertheless, the story could be improved by stressing the interaction between solar radiation or solar irradiance and temperatures, specifically on topics like confounding factors.
The use of the term "mangrove health" can be considered equivalent to the use of the term NDVI. Though NDVI can be considered a good proxy measure for vegetation greenness, it doesn't measure health per se. The authors can be more precise with their word choice throughout the text by perhaps using "canopy greenness," "photosynthetic activity," or "vegetation dynamics."
The exclusion of precipitation as a main variable has been explained (Lines 78–81), but no mention has been made of the possible interaction between precipitation and solar radiation and temperature. For instance, when solar radiation is low, it might be expected that the conditions are associated with high cloudiness and precipitation. Can the correlations with solar radiation possibly be affected by water availability or salinity due to rainfall?
The difference between the three regions along the latitudinal range (Northern, Middle, Southern) is an essential part of the MS. This explanation is supported because it is related to climate factors as well as species. It would have been beneficial if there were more specific climatic factors regarding average winter temperatures and precipitation levels cited regarding each of these regions.
The title is good, but perhaps a small adjustment can be made. "Climate extremes" is employed, yet the work examines mostly the lagged and anomalous aspects rather than extreme ones (such as the lowest 10%). One wonders if maybe the title "Climatic Controls and Extreme Events." would not be more universally descriptive. just my suggestion, not too tied to it.
Abstract
The phrase "positive relations with temperature and solar radiation, particularly in cumulative anomalies on seasonal time scales" is a bit vague. It would be stronger to write the key finding more precisely, e.g., "mangrove growth is strongly influenced by preceding winter temperatures and seasonal solar radiation, with distinct lagged responses across latitudinal zones."
The mention of "low solar radiation events associated with aerosol emissions" is a key conclusion. It would be beneficial to briefly state the scenario under which this is most pronounced (i.e., the high-emission SSP3-7.0 scenario) to add specificity and highlight the policy relevance
The final sentence is good but could be more direct. For example: "This study highlights that both temperature-driven opportunities and solar radiation constraints must be integrated into practical planning for mangrove-based climate solutions.The abstract fails to point out the innovative approach to methodology presented in the study, which uses bootstrapping to investigate the lagged effects, as well as unique events. This represents an area of significant methodological strength, which should at least be referred to in the abstract to draw the reader’s attention to the statistical aspect.
The abstract focused on East Asia, which is actually accurate. Nevertheless, it does not contain information regarding the regional specification of East Asia that was considered in the MS (southern Japan and southern China), which helps give additional context.
Methods
The reference to Table S2 for the list of CMIP6 models appears to be a typo; the list is in Table S1. Please correct this. (The text says Table S2, but the supplementary file has the list in Table S1).
Major Point: The selection criteria for mangrove pixels (≥60% canopy coverage from 1996–2020) is crucial. Why was the period 1996-2020 chosen for canopy stability when the primary analysis period is 2001-2022? Please clarify the rationale for this specific timeframe and the use of the MCD12Q1 product for a coverage threshold, as it is a land cover classification product, not a direct canopy density product.
Major Points: There is a major concern regarding the methodology because of the discrepancy in spatial resolutions. While NDVI has a spatial resolution of 250m x 250m, the spatial resolution of the climate variables provided in the ERA5 dataset is 0.25° x 0.25° (approx. 27.75 km x 27.75 km). There may be thousands of vegetation index pixels within a climate cell encompassing a diverse range of vegetation categories (water bodies, urban landscapes, agricultural lands). Fetching climate information for a 'mangrove formation' without the need for any index calculation may add noise and might reduce the precision of the resulting relationship. Kindly provide a thorough explanation of this choice and the implications of spatial mismatch between variables.
For the forest extraction, a 2 km buffer around undisturbed mangroves was used. What is the justification for this specific buffer distance? How sensitive are the comparative results to the choice of this buffer size?
The analysis uses "monthly detrended anomalies." Please specify the method used for detrending (e.g., linear regression, polynomial fit) and how the anomalies were calculated (e.g., deviation from the monthly long-term mean).
The moving windows in the lag-effect test are specified, such as "MAM NDVI vs. FMA climate factors" when referring to a 1-month lag. This is clear. However, it is also stated that "boreal seasonal composites" are used in the analysis. Could this be further clarified by stating whether the climate data were first averaged into 3-month blocks, for example FMA, and correlated with the seasonal NDVI, MAM, or if the analysis has used monthly data with lagged months?
The critical temperature threshold of 10°C in DJF is adopted from a study in Fujian Province (Wang et al., 2022). While this is a reasonable starting point, this threshold may vary by species and latitude. Please discuss the potential limitations of applying a single threshold derived from one part of the study region (the northern edge) to project expansion across all of East Asia, including Japan and South Korea, which may have different local conditions and species assemblages
Low solar radiation events are defined as values below -1 standard deviation of the long-term mean. This is a standard approach. However, is this based on the mean of the entire historical period (1940-2014) or a moving baseline? Clarifying this is important for interpreting the trend analysis in Figure 4.
In projecting future potential habitats, the method identifies "current non-mangrove shorelines." Please provide more detail on how these shorelines were defined and extracted. Was a specific coastal dataset used? What criteria (e.g., elevation, slope, proximity to the sea) were applied to ensure these are potentially viable areas for mangrove colonization, beyond just meeting the temperature threshold?
Results
The linear regression analysis (Fig. 2a) shows no consistent NDVI response to temperature. This is a surprising but interesting result. The authors should discuss this more. Does this suggest that over the interannual scale, temperature variations within the established thermal niche are not a primary driver of productivity, whereas extreme temperature events (analyzed later) are? This distinction is important.
The finding of a "predominantly positive NDVI responses to solar radiation in the middle and southern zones" (Fig. 2b) is a central result. The authors should highlight the novelty of this finding more strongly, as they correctly state that solar radiation is often considered secondary in mangrove studies.
The results show that high MAM NDVI in the northern zone is linked to warmer preceding winter temperatures (Fig. 3a). This is a clear and well-supported finding. The authors should emphasize this as strong evidence for the legacy effect of winter conditions on the spring growth of temperate-zone mangroves.
The results show an increasing trend of low-radiation events under SSP3-7.0, despite other studies showing a general increase in solar radiation in the region. This is a very interesting paradox. The authors should elaborate on this. Does it imply an increase in the “variability” of solar radiation, with more frequent extreme low events even if the mean increases? This would be a significant finding for ecosystem resilience.
The analysis in Figure 5 suggests that in potential expansion zones, temperature thresholds will be frequently exceeded, while extreme low-radiation events will be limited, even under SSP3-7.0. This seems to slightly contradict the earlier finding that low-radiation events will be an increasing risk. Please clarify this. Does this mean the risk is primarily for “existing” mangrove zones, but not for the “newly suitable” northern zones? This distinction needs to be made explicit.
****PLEASE IN REVISON ADD LINES NUMERS TO MAKE EASY TO COMMENTS.