Abstract
Mangrove forests are a highly productive ecosystem with important potential to offset anthropogenic greenhouse gas emissions. Mangroves are expected to respond differently to climate change compared to terrestrial forests owing to their location in the tidal environment and unique ecophysiological characteristics, but the magnitude of difference remains uncertain at the global scale. Here we use satellite observations to examine mean trends and interannual variability in the productivity of global mangrove forests and nearby terrestrial evergreen broadleaf forests from 2001 to 2020. Although both types of ecosystem experienced significant recent increases in productivity, mangroves exhibited a stronger increasing trend and greater interannual variability in productivity than evergreen broadleaf forests on three-quarters of their co-occurring coasts. The difference in productivity trends is attributed to the stronger CO2 fertilization effect on mangrove photosynthesis, while the discrepancy in interannual variability is attributed to the higher sensitivities to variations in precipitation and sea level. Our results indicate that mangroves will have a faster increase in productivity than terrestrial forests in a CO2-rich future but may suffer more from deficits in water availability, highlighting a key difference between terrestrial and tidal ecosystems in their responses to climate change.
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All data used in this study are publicly available. The MODIS 250 m spectral reflectance data (MOD13Q1 and MYD13Q1) are available at https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1 and https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MYD13Q1. Gridded climate data used in this study are available in Supplementary Table 2. Forest cover data can be found at the following websites: Global Mangrove Watch v.3.0 (https://zenodo.org/record/6894273), MCD12Q1 land cover product (https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MCD12Q1) and global forest change map (https://developers.google.com/earth-engine/datasets/catalog/UMD_hansen_global_forest_change_2021_v1_9). ECOSTRESS evapotranspiration data can be accessed at https://www.jpl.nasa.gov/missions/ecosystem-spaceborne-thermal-radiometer-experiment-on-space-station-ecostress. Atmospheric CO2 concentration recorded by the Mauna Loa Observatory can be accessed at https://gml.noaa.gov/ccgg/trends/data.html. The GPP measurements in the three mangrove sites are available in Supplementary Table 1.
Code availability
The code used to analyse these data and generate the results presented in this study can be obtained from https://github.com/GIS-ZhangZhen/MangroveGreenness.
References
Bunting, P. et al. Global mangrove extent change 1996–2020: Global Mangrove Watch version 3.0. Remote Sens. 14, 3657 (2022).
Lovelock, C. E. & Reef, R. Variable impacts of climate change on blue carbon. One Earth 3, 195–211 (2020).
Lee, S. Y. et al. Ecological role and services of tropical mangrove ecosystems: a reassessment. Glob. Ecol. Biogeogr. 23, 726–743 (2014).
Taillardat, P., Friess, D. A. & Lupascu, M. Mangrove blue carbon strategies for climate change mitigation are most effective at the national scale. Biol. Lett. 14, 20180251 (2018).
Donato, D. C. et al. Mangroves among the most carbon-rich forests in the tropics. Nat. Geosci. 4, 293–297 (2011).
Friess, D. A., Adame, M. F., Adams, J. B. & Lovelock, C. E. Mangrove forests under climate change in a 2 °C world. Wiley Interdiscip. Rev. Clim. Change 13, e792 (2022).
Dahdouh-Guebas, F. et al. Cross-cutting research themes for future mangrove forest research. Nat. Plants 8, 1131–1135 (2022).
Duke, N. C. et al. Large-scale dieback of mangroves in Australia. Mar. Freshw. Res. 68, 1816 (2017).
Saintilan, N. et al. The lunar nodal cycle controls mangrove canopy cover on the Australian continent. Sci. Adv. 8, eabo6602 (2022).
Ruehr, S. et al. Evidence and attribution of the enhanced land carbon sink. Nat. Rev. Earth Environ. 4, 518–534 (2023).
Chen, C., Riley, W. J., Prentice, I. C. & Keenan, T. F. CO2 fertilization of terrestrial photosynthesis inferred from site to global scales. Proc. Natl Acad. Sci. USA 119, e2115627119 (2022).
Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2020).
Ball, M. C. in Tropical Forest Plant Ecophysiology (eds Mulkey, S. S. et al.) 461–496 (Springer, 1996).
Lovelock, C. E., Krauss, K. W., Osland, M. J., Reef, R. & Ball, M. C. in Tropical Tree Physiology Vol. 6 (eds Goldstein, G. & Santiago, L.) 149–179 (Springer, 2016).
Cui, X. et al. Stronger ecosystem carbon sequestration potential of mangrove wetlands with respect to terrestrial forests in subtropical China. Agric. For. Meteorol. 249, 71–80 (2018).
Naskar, S. & Palit, P. K. Anatomical and physiological adaptations of mangroves. Wetl. Ecol. Manag. 23, 357–370 (2015).
Srikanth, S., Lum, S. K. Y. & Chen, Z. Mangrove root: adaptations and ecological importance. Trees 30, 451–465 (2016).
Liang, J. et al. Evapotranspiration characteristics distinct to mangrove ecosystems are revealed by multiple‐site observations and a modified two‐source model. Water Resour. Res. 55, 11250–11273 (2019).
Sperry, J. S., Tyree, M. T. & Donnelly, J. R. Vulnerability of xylem to embolism in a mangrove vs an inland species of Rhizophoraceae. Physiol. Plant. 74, 276–283 (1988).
Kumar, D. & Scheiter, S. Biome diversity in South Asia—how can we improve vegetation models to understand global change impact at regional level? Sci. Total Environ. 671, 1001–1016 (2019).
Ward, N. D. et al. Representing the function and sensitivity of coastal interfaces in Earth system models. Nat. Commun. 11, 2458 (2020).
LaFond-Hudson, S. & Sulman, B. Modeling strategies and data needs for representing coastal wetland vegetation in land surface models. New Phytol. 238, 938–951 (2023).
Badgley, G., Field, C. B. & Berry, J. A. Canopy near-infrared reflectance and terrestrial photosynthesis. Sci. Adv. 3, e1602244 (2017).
Zeng, Y. et al. Optical vegetation indices for monitoring terrestrial ecosystems globally. Nat. Rev. Earth Environ. 3, 477–493 (2022).
Wang, S. et al. Recent global decline of CO2 fertilization effects on vegetation photosynthesis. Science 370, 1295–1300 (2020).
Saintilan, N., Wilson, N. C., Rogers, K., Rajkaran, A. & Krauss, K. W. Mangrove expansion and salt marsh decline at mangrove poleward limits. Glob. Change Biol. 20, 147–157 (2014).
Cavanaugh, K. C. et al. Climate-driven regime shifts in a mangrove–salt marsh ecotone over the past 250 years. Proc. Natl Acad. Sci. USA 116, 21602–21608 (2019).
Good, S. P., Moore, G. W. & Miralles, D. G. A mesic maximum in biological water use demarcates biome sensitivity to aridity shifts. Nat. Ecol. Evol. 1, 1883–1888 (2017).
Modak, A. & Mauritsen, T. The 2000–2012 global warming hiatus more likely with a low climate sensitivity. Geophys. Res. Lett. 48, e2020GL091779 (2021).
Ogle, K. et al. Quantifying ecological memory in plant and ecosystem processes. Ecol. Lett. 18, 221–235 (2015).
Ballantyne, A. et al. Accelerating net terrestrial carbon uptake during the warming hiatus due to reduced respiration. Nat. Clim. Change 7, 148–152 (2017).
Peters, W. et al. An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker. Proc. Natl Acad. Sci. USA 104, 18925–18930 (2007).
Adler, R. F., Gu, G., Sapiano, M., Wang, J.-J. & Huffman, G. J. Global precipitation: means, variations and trends during the satellite era (1979–2014). Surv. Geophys. 38, 679–699 (2017).
Jacotot, A., Marchand, C., Gensous, S. & Allenbach, M. Effects of elevated atmospheric CO2 and increased tidal flooding on leaf gas-exchange parameters of two common mangrove species: Avicennia marina and Rhizophora stylosa. Photosynth. Res. 138, 249–260 (2018).
Ruan, L., Yan, M., Zhang, L., Fan, X. & Yang, H. Spatial-temporal NDVI pattern of global mangroves: a growing trend during 2000–2018. Sci. Total Environ. 844, 157075 (2022).
Chapman, S. K. et al. Mangrove growth response to experimental warming is greatest near the range limit in northeast Florida. Ecology 102, e03320 (2021).
Cavanaugh, K. C. et al. Sensitivity of mangrove range limits to climate variability. Glob. Ecol. Biogeogr. 27, 925–935 (2018).
Yao, Q. et al. Mangrove expansion at poleward range limits in North and South America: Late-Holocene climate variability or anthropocene global warming? Catena 216, 106413 (2022).
Saintilan, N. & Rogers, K. Woody plant encroachment of grasslands: a comparison of terrestrial and wetland settings. New Phytol. 205, 1062–1070 (2015).
Gu, X. et al. Changes in mangrove blue carbon under elevated atmospheric CO2. Ecosyst. Health Sustain. 9, 0033 (2023).
Ainsworth, E. A. & Rogers, A. The response of photosynthesis and stomatal conductance to rising [CO2]: mechanisms and environmental interactions. Plant Cell Environ. 30, 258–270 (2007).
Ainsworth, E. A. & Long, S. P. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol. 165, 351–372 (2005).
Piao, S. et al. Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends. Glob. Change Biol. 19, 2117–2132 (2013).
Terrer, C., Vicca, S., Hungate, B. A., Phillips, R. P. & Prentice, I. C. Mycorrhizal association as a primary control of the CO2 fertilization effect. Science 353, 72–74 (2016).
Pan, Y. et al. Contrasting responses of woody and grassland ecosystems to increased CO2 as water supply varies. Nat. Ecol. Evol. 6, 315–323 (2022).
Drake, B. G., Gonzàlez-Meler, M. A. & Long, S. P. More efficient plants: a consequence of rising atmospheric CO2? Annu. Rev. Plant Physiol. Plant Mol. Biol. 48, 609–639 (1997).
Krauss, K. W. et al. Mangroves provide blue carbon ecological value at a low freshwater cost. Sci. Rep. 12, 17636 (2022).
Maschler, J. et al. Links across ecological scales: plant biomass responses to elevated CO2. Glob. Change Biol. 28, 6115–6134 (2022).
Hayes, M. A. et al. Foliar water uptake by coastal wetland plants: a novel water acquisition mechanism in arid and humid subtropical mangroves. J. Ecol. 108, 2625–2637 (2020).
Fisher, J. B. et al. ECOSTRESS: NASA’s next generation mission to measure evapotranspiration from the International Space Station. Water Resour. Res. 56, e2019WR026058 (2020).
Lagomasino, D. et al. Storm surge and ponding explain mangrove dieback in southwest Florida following Hurricane Irma. Nat. Commun. 12, 4003 (2021).
Abhik, S. et al. Influence of the 2015–2016 El Niño on the record-breaking mangrove dieback along northern Australia coast. Sci. Rep. 11, 20411 (2021).
Yim, M. W. & Tam, N. F. Y. Effects of wastewater-borne heavy metals on mangrove plants and soil microbial activities. Mar. Pollut. Bull. 39, 8 (1999).
Passioura, J. B., Ball, M. C. & Knight, J. H. Mangroves may salinize the soil and in so doing limit their transpiration rate. Funct. Ecol. 6, 476 (1992).
Ball, M. C. Ecophysiology of mangroves. Trees 2, 129–142 (1988).
Zhang, Y. et al. Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO2. Nat. Commun. 13, 4875 (2022).
Ahlström, A. et al. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348, 895–899 (2015).
Poulter, B. et al. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509, 600–603 (2014).
Huang, K. & Xia, J. High ecosystem stability of evergreen broadleaf forests under severe droughts. Glob. Change Biol. 25, 3494–3503 (2019).
Zhu, X., Sun, C. & Qin, Z. Drought‐induced salinity enhancement weakens mangrove greenhouse gas cycling. J. Geophys. Res. Biogeosci. 126, e2021JG006416 (2021).
Méndez-Alonzo, R., López-Portillo, J., Moctezuma, C., Bartlett, M. K. & Sack, L. Osmotic and hydraulic adjustment of mangrove saplings to extreme salinity. Tree Physiol. 36, 1562–1572 (2016).
Hoppe-Speer, S. C. L., Adams, J. B., Rajkaran, A. & Bailey, D. The response of the red mangrove Rhizophora mucronata Lam. to salinity and inundation in South Africa. Aquat. Bot. 95, 71–76 (2011).
Reef, R., Feller, I. C. & Lovelock, C. E. Nutrition of mangroves. Tree Physiol. 30, 1148–1160 (2010).
Anderegg, W. R. L. et al. Hydraulic diversity of forests regulates ecosystem resilience during drought. Nature 561, 538–541 (2018).
Liu, D., Wang, T., Peñuelas, J. & Piao, S. Drought resistance enhanced by tree species diversity in global forests. Nat. Geosci. 15, 800–804 (2022).
Hochard, J. P., Hamilton, S. & Barbier, E. B. Mangroves shelter coastal economic activity from cyclones. Proc. Natl Acad. Sci. USA 116, 12232–12237 (2019).
Lovelock, C. E., Feller, I. C., Reef, R., Hickey, S. & Ball, M. C. Mangrove dieback during fluctuating sea levels. Sci. Rep. 7, 1680 (2017).
Wang, X. et al. Rebound in China’s coastal wetlands following conservation and restoration. Nat. Sustain. 4, 1076–1083 (2021).
Mengistu, A. G. et al. Sun-induced fluorescence and near-infrared reflectance of vegetation track the seasonal dynamics of gross primary production over Africa. Biogeosciences 18, 2843–2857 (2021).
Zhang, J. et al. NIRv and SIF better estimate phenology than NDVI and EVI: effects of spring and autumn phenology on ecosystem production of planted forests. Agric. For. Meteorol. 315, 108819 (2022).
Barr, J. G. et al. Controls on mangrove forest–atmosphere carbon dioxide exchanges in western Everglades National Park. J. Geophys. Res. Biogeosci. 115, G02020 (2010).
Zhu, X. et al. Potential of sun-induced chlorophyll fluorescence for indicating mangrove canopy photosynthesis. J. Geophys. Res. Biogeosci. 126, e2020JG006159 (2021).
Liu, J., Valach, A., Baldocchi, D. & Lai, D. Y. F. Biophysical controls of ecosystem‐scale methane fluxes from a subtropical estuarine mangrove: multiscale, nonlinearity, asynchrony and causality. Glob. Biogeochem. Cycles 36, e2021GB007179 (2022).
Feagin, R. A. et al. Tidal wetland gross primary production across the continental United States, 2000–2019. Glob. Biogeochem. Cycles 34, e2019GB006349 (2020).
Rienecker, M. M. et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Clim. 24, 3624–3648 (2011).
Du, J. et al. Global satellite retrievals of the near-surface atmospheric vapor pressure deficit from AMSR-E and AMSR2. Remote Sens. 10, 1175 (2018).
Huffman, G. J. et al. The Global Precipitation Climatology Project (GPCP) combined precipitation dataset. Bull. Am. Meteorol. Soc. 78, 5–20 (1997).
Osland, M. J. et al. Climatic controls on the global distribution, abundance, and species richness of mangrove forests. Ecol. Monogr. 87, 341–359 (2017).
Rovai, A. S. et al. Macroecological patterns of forest structure and allometric scaling in mangrove forests. Glob. Ecol. Biogeogr. 30, 1000–1013 (2021).
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).
Funk, C. et al. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci. Data 2, 150066 (2015).
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).
Keeling, C. D. et al. Atmospheric carbon dioxide variations at Mauna Loa Observatory, Hawaii. Tellus 28, 538–551 (1976).
Chen, Y. & Kirwan, M. L. Climate-driven decoupling of wetland and upland biomass trends on the mid-Atlantic coast. Nat. Geosci. 15, 913–918 (2022).
Zhou, L. et al. Widespread decline of Congo rainforest greenness in the past decade. Nature 509, 86–90 (2014).
Sulla-Menashe, D., Gray, J. M., Abercrombie, S. P. & Friedl, M. A. Hierarchical mapping of annual global land cover 2001 to present: the MODIS Collection 6 Land Cover product. Remote Sens. Environ. 222, 183–194 (2019).
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Berner, L. T. et al. Summer warming explains widespread but not uniform greening in the Arctic tundra biome. Nat. Commun. 11, 4621 (2020).
Chen, C. et al. China and India lead in greening of the world through land-use management. Nat. Sustain. 2, 122–129 (2019).
Winkler, A. J. et al. Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2. Biogeosciences 18, 4985–5010 (2021).
Cortés, J. et al. Where are global vegetation greening and browning trends significant? Geophys. Res. Lett. 48, e2020GL091496 (2021).
Yuan, W. et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth. Sci. Adv. 5, eaax1396 (2019).
Kirwan, M. L. & Gedan, K. B. Sea-level driven land conversion and the formation of ghost forests. Nat. Clim. Change 9, 450–457 (2019).
Medhaug, I., Stolpe, M. B., Fischer, E. M. & Knutti, R. Reconciling controversies about the ‘global warming hiatus’. Nature 545, 41–47 (2017).
Seddon, A. W. R., Macias-Fauria, M., Long, P. R., Benz, D. & Willis, K. J. Sensitivity of global terrestrial ecosystems to climate variability. Nature 531, 229–232 (2016).
Perri, S., Katul, G. G. & Molini, A. Xylem–phloem hydraulic coupling explains multiple osmoregulatory responses to salt stress. New Phytol. 224, 644–662 (2019).
Acknowledgements
Yangfan Li is the main corresponding author of the study. Yangfan Li and Z.Z. acknowledge support from the National Natural Science Foundation of China (Grant No. 42276232), the Internal Program of State Key Laboratory of Marine Environmental Science (Grant No. MELRI2205) and the China Scholarship Council (Grant No. 202106310079). X.L. acknowledges support from the Singapore Ministry of Education (Grant No. A-0003625-00-00) and the Singapore Energy Center core project (Grant No. A-8000179-00-00). D.A.F. thanks Michael and Mathilda Cochran for endowing the Cochran Family Professorship in Earth and Environmental Sciences at Tulane University. We thank N. Xu at Hohai University for his feedback on an earlier version of this work.
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Z.Z. conceptualized the study. Z.Z., X.L. and Yangfan Li designed the research. Z.Z. performed the analysis and drafted the initial manuscript. X.L. substantially revised the paper. D.A.F., S.W., Yi Li and Yangfan Li contributed to result interpretation and made substantial contributions to manuscript refinement.
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Extended data
Extended Data Fig. 1 The correlation between NIRv and GPP at three mangrove flux sites.
The red lines give the fitted mean linear relationship between NIRv and GPP. Shading indicates the 95% confidence intervals estimated by bootstrapping (n = 1000). P values were determined through two-sided Pearson’s correlation significance test.
Extended Data Fig. 2 Temporal variations in NIRv of mangroves and EBFs and environmental factors in coastal grids.
a-e, Time variations in annual NIRv for mangroves and EBFs over the globe, America, Africa, Asia, and Oceania, respectively. NIRv are normalized by the long-term average. The dashed lines give the overall linear trend. The trend rates in the legend were computed from the Theil-Sen slope estimator. P values were determined through two-sided Mann-Kendall trend test. Shading indicates the 95% confidence intervals estimated by bootstrapping (n = 1000). f-j, Interannual fluctuances in annual detrended NIRv for mangroves and EBFs over the globe, America, Africa, Asia, and Oceania, respectively. The numbers in the legend indicate the coefficient of variation of each NIRv time series to reflect the interannual variability. k-o, Time variations in annual temperature, precipitation and sea-level anomaly for the coastal grids over the globe, America, Africa, Asia, and Oceania, respectively.
Extended Data Fig. 3 Time series of annual NIRv (a) and environmental factors (air temperature, precipitation, and sea-level anomaly) (b) in the Gulf of Carpentaria, Australia.
Temperature, precipitation and sea-level anomaly is from MERRA2, GPCP, and CMEMS datasets, respectively. Shaded areas show ±1 standard deviation of the mean.
Extended Data Fig. 4 The comparisons between mangroves and EBFs in their ecohydrological properties.
Differences in marginal biological water use fraction (∂Tc/∂P) (a) and marginal water use efficiency (MWUE) (b). All comparisons were performed under controlled geographical conditions using the two-sided paired t-test to eliminate spatial mismatch. Error bars show 95% confidence intervals estimated by bootstrapping (n = 1000), and the dots represent the average values.
Extended Data Fig. 5 eCO2-induced NIRv trends calculated using factorial simulation.
The right panels depict the latitudinal pattern of trends averaged per 1° latitude band.
Extended Data Fig. 6 Simulated NIRv trends for mangroves and EBFs, respectively.
a, Temperature-contributed NIRv trends. b, VPD-contributed NIRv trends. The right panels depict the latitudinal pattern of trends averaged per 1° latitude band.
Extended Data Fig. 7 Model performance in simulating observed difference in NIRv IAV and trend between mangroves and EBFs.
a,c, Comparison of ΔIAV between observed and simulated from climate forcing data 1 (a) and climate forcing data 2 (c). b,d, Comparison of Δtrend between observed and simulated from climate forcing data 1 (b) and climate forcing data 2 (d). Climate forcing data 1 represents factors from MERRA2, GPCP, and NOAA CarbonTracker CT2022 datasets. Climate forcing data 2 represents factors from ERA5, CHIRPS, TerraClimate and Mauna Loa observatory. Scatter refers to each paired coastal grid cell (n = 1475). The red shaded areas show 95% confidence intervals for the regression fits. P values were determined through one-sided F-test.
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Zhang, Z., Luo, X., Friess, D.A. et al. Stronger increases but greater variability in global mangrove productivity compared to that of adjacent terrestrial forests. Nat Ecol Evol 8, 239–250 (2024). https://doi.org/10.1038/s41559-023-02264-w
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