Carbon fluxes are the currency of the terrestrial carbon cycle. Gross primary productivity, or GPP, quantifies the total carbon dioxide that plants strip from the air through photosynthesis. Ecosystem respiration, ER, counts the carbon returned to the atmosphere as plants, microbes, and soils break down organic matter. The difference between these two large opposing flows — net ecosystem productivity, NEP — reveals whether an ecosystem functions as a carbon sink or a carbon source. Pinning these terms down is far from academic: the terrestrial biosphere absorbs a substantial share of humanity’s carbon emissions each year, yet the strength of that sink varies enormously between regions and years, and some of the largest uncertainties in the global carbon budget lie in exactly the kind of heterogeneous, human-dominated landscapes that characterize the U.S. East Coast, where fragmented forests, agricultural land, tidal wetlands, and sprawling metropolitan areas intermingle within a few hundred kilometres of coastline.

The ground truth for the new models comes from eddy covariance, the gold-standard technique for measuring ecosystem-scale gas exchange. Towers rising above the canopy carry fast-response sonic anemometers and infrared gas analysers that record vertical wind speed and carbon dioxide concentration dozens of times per second. Because turbulent eddies continuously shuttle air between the surface and the atmosphere, the covariance between fluctuations in vertical wind and fluctuations in the CO2 mixing ratio yields a direct, continuous measurement of net exchange over a footprint of roughly a square kilometre. Networks such as FLUXNET and its North American branch AmeriFlux, whose contribution the authors gratefully acknowledge, have accumulated decades of such records worldwide. The catch is that a tower sees only its own footprint; extending those point measurements into wall-to-wall regional maps requires models that translate satellite observations and meteorological reanalysis into flux estimates — the very task the Shanghai Ocean University team set out to improve.

To build that translation engine, the researchers assembled a multi-scale dataset spanning roughly twenty years along the East Coast. Tower observations of carbon fluxes were fused with vegetation products from NASA’s MODIS sensors aboard the Terra and Aqua satellites and with ERA5-Land, the state-of-the-art global reanalysis dataset produced by the Copernicus Climate Change Service and the European Centre for Medium-Range Weather Forecasts, which integrates vast streams of observations into a physically consistent land-surface record. Before any machine learning began, the team screened candidate environmental variables with correlation analysis and with the Geodetector method, a spatial-statistics technique that quantifies how much of the spatial heterogeneity in a target variable can be explained by stratifying the landscape according to a potential driver. Unlike correlation alone, Geodetector captures nonlinear relationships and interactions without assuming any particular functional form, which makes it well suited to disentangling the tangled influences of climate, vegetation, and terrain on carbon exchange across sharply contrasting ecosystem types.

That screening produced a winning recipe of eight predictors: T2M, the two-metre air temperature; VPD, the vapour pressure deficit that measures how thirsty the atmosphere is; SSRD, the downward solar radiation that powers photosynthesis; EVI, the enhanced vegetation index that tracks canopy greenness from space; LSWI, the land surface water index that reflects vegetation and soil moisture; LAI, the leaf area index describing how much photosynthetic surface the canopy exposes; EVAVT, an evaporation-related variable; and DEM, the digital elevation model that encodes terrain and elevation. Each predictor represents a distinct physiological lever. Temperature and radiation set the pace of the enzymatic machinery of photosynthesis and respiration; VPD governs whether leaf stomata stay open or clamp shut to conserve water; and the satellite-derived vegetation indices record the structural and phenological state of the canopy itself. When this eight-factor combination was fed into the models, it delivered the most accurate and stable flux estimates of any input set the team tested, a result that held across ecosystem types and across all three carbon fluxes.

With the inputs fixed, the researchers staged a head-to-head contest between four widely used machine-learning algorithms: random forest (RF), artificial neural network (ANN), support vector regression (SVR), and extreme gradient boosting (XGBoost). Each brings a different inductive bias. Random forests grow hundreds of decision trees on random subsets of the data and average their predictions, a bootstrap-aggregation strategy that suppresses overfitting. Neural networks stack layers of weighted neurons that can approximate highly nonlinear functions but demand careful tuning and abundant training data. Support vector regression fits a margin-tolerant function in a high-dimensional kernel space, while XGBoost builds trees sequentially, each new tree correcting the residual errors left by its predecessors. Under identical input combinations, the random forest emerged as the consistent champion for GPP, NEP, and ER alike. The outcome suggests that the ensemble’s robustness to noisy inputs and its resistance to overfitting on heterogeneous, multi-decadal observations outweigh the theoretical flexibility of the more elaborate architectures for this regional estimation problem.

The verification statistics are the study’s headline numbers. The trained models achieved coefficients of determination — R² values — of 0.88 for gross primary productivity, 0.81 for ecosystem respiration, and 0.55 for net ecosystem productivity against independent observations. Benchmark models from FLUXCOM, the leading international initiative that upscales eddy covariance data into continuous global flux products, achieve R² values of only 0.61, 0.57, and 0.28 for the same three fluxes. In practical terms, the new models explain roughly 88 percent of the observed variance in photosynthetic carbon uptake where the existing standard explains about 61 percent, and they nearly double the explained variance for the net sink term. NEP remains the hardest target for any modelling approach, and for an instructive reason: it is a small residual obtained by subtracting two enormous numbers, so even modest independent errors in GPP and ER compound into a large relative error in their difference. Even so, leaping from 0.28 to 0.55 transforms a product of marginal utility into one capable of resolving meaningful spatial and interannual variation.

Perhaps the most consequential scientific insight lies in the variable-importance analysis. Across every ecosystem type examined, the enhanced vegetation index ranked as the single most important driver of carbon-flux variability, elevating vegetation growth status above temperature, radiation, and atmospheric dryness as the master control on carbon exchange along the East Coast. The interpretation becomes intuitive once spelled out: photosynthesis and respiration are both carried out by the canopy and the organisms it sustains, so the state of the vegetation — how green it is, how much leaf area it displays, how its phenology unfolds through the seasons — effectively sets the stage on which all the climatic actors perform. Climate variables still matter, and the prominence of vapour pressure deficit echoes a growing body of evidence that atmospheric drought is an increasingly dominant brake on carbon uptake as the planet warms. But the finding suggests that satellite observations of greenness, already among the most widely available remote-sensing products, carry exceptional predictive power for regional carbon monitoring.

Beyond the headline accuracy, the framework hands researchers and policymakers a two-decade, multi-scale portrait of how carbon moves through one of the most economically and ecologically important regions of North America, resolving spatiotemporal patterns across ecosystem types that coarse global products tend to blur. Such maps can inform forest management and coastal restoration decisions, provide benchmarks against which Earth system models can be evaluated, and support the emerging carbon-accounting infrastructure that depends on credible, spatially explicit baselines. The authors note that the underlying data will be made available from the corresponding author upon reasonable request, and they report that the work proceeded without dedicated external funding. Limitations remain, most notably the difficulty of the net flux term and the dependence of any upscaled product on the density and quality of tower coverage. What the study ultimately delivers is a methodological template: pair rigorous driver screening with carefully benchmarked machine learning, ground everything in decades of direct flux measurement, and the breathing of entire landscapes becomes not just measurable at a handful of towers, but legible across an entire coastline, every day of the year.

Salt marshes, coastal wetlands found in the intertidal zones of estuaries and bays, play a crucial role in the carbon cycle. These ecosystems are characterized by their dense vegetation and waterlogged soils, conditions that slow down the decomposition of organic matter and allow for significant carbon storage in the form of what scientists refer to as “blue carbon.” Blue carbon is carbon captured by oceanic and coastal ecosystems, including salt marshes, mangroves, and seagrass beds. The potential of these ecosystems to mitigate climate change by locking away atmospheric carbon dioxide has been touted as a natural climate solution. However, as the study highlights, this potential is under serious threat.

The researchers employed a comprehensive global dataset combining satellite imagery, field measurements, and carbon flux modeling to quantify carbon emissions and sequestration rates in salt marshes worldwide. By integrating these diverse data sources over recent decades, the study provides an unprecedentedly detailed account of the net carbon balance of salt marshes on a global scale. The key finding is unsettling: anthropogenic pressures and environmental changes have led to blue carbon losses that outpace the gains from restoration projects implemented to date.

One of the most compelling revelations of the study is the scale of salt marsh degradation driving these carbon losses. Factors such as coastal development, land reclamation, pollution, and rising sea levels contribute to the fragmentation and dieback of salt marsh habitats. The study documents that the accelerated destruction of marshlands results in the release of carbon stored for centuries back into the atmosphere, thereby exacerbating the greenhouse effect. This overturns the previously held assumption that restoration efforts have been sufficient to compensate for these losses.

This imbalance between loss and restoration gains challenges policymakers and conservationists alike. Restoration activities typically focus on replanting native vegetation and improving hydrological conditions to mimic natural system functions. While these strategies are essential, the study argues that their scope and scale are currently inadequate against the backdrop of ongoing marsh degradation. Restoration projects, often limited by funding, technological challenges, and local governance issues, have not yet achieved the footprint necessary to reverse net carbon emissions effectively.

Moreover, the study highlights the influence of climate change itself on both the functionality and resilience of salt marshes. Sea level rise, shifting precipitation patterns, and increasing storm frequencies are altering marsh hydrology and sediment budgets, which are critical for marsh accretion and stability. As these physical forcings intensify, they pose profound threats to the ability of marshes to continue acting as carbon sinks. The feedback loops between climate change impacts and marsh degradation may create scenarios where restoration alone cannot keep pace.

Importantly, the authors emphasize the heterogeneity of salt marsh responses globally. Regions vary in their susceptibility to stressors and in the effectiveness of restoration interventions. For instance, marshes in North America show more robust restoration gains compared to those in Asia, where urban expansion and industrial activities are more aggressive. This spatial variability calls for tailored management approaches that match local ecological, social, and economic contexts.

The paper also delves into new methodologies for improving restoration outcomes. The integration of remote sensing technologies with carbon flux measurements allows for finer-scale monitoring and adaptive management. Innovative restoration techniques, such as sediment augmentation and engineered hydrologic reestablishment, are discussed as potential pathways to enhance carbon sequestration capacities. However, the authors caution that despite technological progress, restoration must align with broader environmental policies targeting pollution reduction and coastal zone management.

The global implications of these findings extend beyond academic circles. Blue carbon ecosystems are increasingly incorporated into national carbon accounting frameworks as countries seek to meet their climate targets under international agreements such as the Paris Accord. The revelation that current blue carbon losses overshadow restoration gains signals a need for reevaluation of policy frameworks and investment priorities. It raises urgent questions about the scalability of blue carbon projects and their role as a reliable climate mitigation strategy without addressing root causes of ecosystem degradation.

In this context, the study advocates for integrative coastal zone management that harmonizes conservation, sustainable development, and climate adaptation. Cross-sectoral collaboration involving scientists, local communities, industries, and governments is vital to safeguard salt marsh ecosystems effectively. The authors propose that protecting existing marshes may be more cost-effective and beneficial for carbon storage than relying primarily on restoration after damage occurs.

Furthermore, this research calls attention to the temporal dimensions of carbon cycling in salt marshes. Carbon sequestration is a slow process occurring over decades to centuries, whereas carbon loss from degradation can be abrupt and large-scale. This asymmetry necessitates long-term monitoring and commitment to environmental stewardship beyond short electoral cycles. Only through sustained, evidence-based actions can the global community hope to maintain the blue carbon benefits provided by salt marshes.

The study also contributes to broader ecosystem service valuation by quantifying the carbon costs of salt marsh decline. By translating ecological changes into climate-relevant metrics, it supports the economic case for prioritizing these habitats in climate policy. The authors encourage the incorporation of blue carbon considerations into spatial planning and investment decisions, highlighting the avoided emissions benefits of salt marsh conservation.

Finally, this pioneering investigation by Zheng and colleagues sets a new benchmark for coastal ecosystem research. It bridges knowledge gaps by connecting local-scale observations with global patterns and policy implications. The work urges a paradigm shift from isolated restoration efforts toward integrated climate-smart management of salt marshes and other blue carbon ecosystems. This holistic approach is crucial for harnessing their full potential to combat climate change and for sustaining the biodiversity and livelihoods dependent on these invaluable coastal environments.

As the world confronts the escalating climate crisis, this study serves as a crucial reminder that the path to a sustainable future must include robust protection and thoughtful management of natural carbon sinks like salt marshes. The challenge is formidable but clear—only by securing and expanding these blue carbon reservoirs can we hope to offset the anthropogenic carbon emissions driving planetary warming. This work not only advances scientific understanding but also energizes global action towards preserving nature’s climate solutions before it is too late.

Subject of Research: Global blue carbon losses and restoration gains in salt marsh ecosystems

Article Title: Global blue carbon losses from salt marshes exceed restoration gains

Article References:
Zheng, Y., Jiang, Q., He, Q. et al. Global blue carbon losses from salt marshes exceed restoration gains. Nat Commun 17, 3744 (2026). https://doi.org/10.1038/s41467-026-70158-z

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41467-026-70158-z