This study systematically evaluated the contribution of UAV LiDAR structural features such as crop height (CH) and multi-layer gap fraction (GF) and the amplitude of the returning signal represented by normalized intensity (INT), together with multispectral (MS) and thermal infrared (TIR) observations for aboveground biomass (AGB) estimation in winter wheat using a common artificial neural network (ANN) framework. Among the evaluated single sensor approaches, LiDAR features consistently provided the strongest performance, demonstrating the complementary value of crop height, vertically distributed canopy density, and normalized LiDAR intensity for characterizing canopy structure and within-canopy variability. Multi-layer GF improved AGB estimation relative to conventional ground-based GF approaches, highlighting the importance of incorporating the vertical distribution of canopy density. Multi-sensor fusion produced only modest additional improvements, indicating limited benefits relative to the increased acquisition and processing requirements. Temporal analysis showed that structural LiDAR features were most informative during early crop development, whereas normalized intensity, spectral reflectance, and thermal observations became increasingly valuable during canopy maturation and senescence. Comparisons with destructively measured plant area index (PAI), leaf area index (LAI), green leaf area index (GLAI), and green fraction of LAI further demonstrated that normalized LiDAR intensity (903 nm) was more closely associated with green canopy components than purely structural LiDAR metrics. Overall, the results demonstrate that fully exploiting both the structural and spectral information contained within LiDAR observations can substantially improve UAV-based biomass estimation, while multispectral and thermal observations provide complementary information whose contribution varies with crop development and monitoring objectives.
Europe's forests store nearly 40 PgC and provide a critical carbon sink of ∼ 0.2 PgC yr−1, yet climate-sensitive disturbances increasingly threaten this capacity. Although disturbance rates from windthrow and bark beetle outbreaks have risen in recent decades, it remains unclear whether these events increasingly affect the oldest and largest trees, which store a disproportionate share of carbon. Focusing on bark beetle outbreaks and windthrow, the dominant natural disturbance agents in temperate and boreal European forests, we combine three decades of satellite-derived disturbance maps with spatially explicit data on forest age, biomass, and species composition to reveal patterns of structural selectivity across Europe. We show that natural disturbances have shifted toward older, carbon-rich forest patches, with disturbed forest area >60 years old nearly tripling since 2010 (from 0.38 to 1.06 Mha). This pattern reflects a qualitative shift in disturbance dynamics, from historically episodic, wind-dominated impacts to increasingly persistent, climate-amplified bark beetle outbreaks that preferentially affect mature spruce forests in Central Europe (effect size = 1.1). As a result, biomass losses from natural disturbances in spruce forests increased fivefold between the early (2011–2016) and recent (2017–2023) periods, outpacing the expansion of the disturbed area. Trend-based projections indicate that, if current patterns of structural selectivity persist, natural disturbances could expose biomass carbon stocks equivalent to approximately 20 % of Europe's contemporary forest carbon sink by 2040 (∼ 0.05 PgC yr−1 or ∼ 0.8 PgC cumulative). Our findings reveal a previously unquantified structural susceptibility: climate-sensitive disturbances increasingly affect forest structures with high per-hectare carbon stocks, amplifying disturbance-related carbon susceptibility and weakening the long-term effectiveness of Europe's forest carbon sink. Adaptive management strategies that promote structural and compositional diversification in high-risk regions will be critical to stabilise forest carbon storage under continued climate change.
East Asian dust outbreaks are accompanied by pronounced synoptic circulation anomalies, yet their influence on phytoplankton variability through atmospheric forcing remains poorly understood. Here we investigate the response of chlorophyll a (Chl a) to spring dust events in the Chinese marginal seas during 2003–2023 using daily anomalies from reanalysis products and a reconstructed Chl a dataset. We find contrasting Chl a responses to dust synoptic events between the Northern and Southern Chinese marginal seas. Under high dust conditions, the Northern Region exhibits an initial Chl a suppression followed by a positive anomaly persisting for about one week, while the south shows an immediate positive response that gradually weakens. These distinct patterns are associated with ocean mixed-layer depth (MLD) adjustments driven by dust-related synoptic circulation. Over the northern seas, Mongolian cyclones produce positive air–sea temperature and humidity gradients through anomalous southerly winds, thus reducing upward latent and sensible heat fluxes and promoting net ocean heat gain and initial mixed-layer shoaling before subsequent deepening. In contrast, southern dust events are associated with migrating anticyclones that drive strong northeasterly winds, generating negative air–sea thermal and moisture gradients and intensified upward latent heat flux, thereby promoting net ocean heat loss and mixed-layer deepening. Net surface heat flux exhibits the strongest negative correlation with MLD at a 1 d lag in both regions, and surface heat loss-driven mixed-layer deepening generally coincides with elevated Chl a anomalies. These results highlight synoptic-scale atmospheric forcing and air–sea heat exchange as important physical pathways linking dust variability to short-term Chl a changes in the Chinese marginal seas.
Nickel (Ni) is an essential micronutrient for marine microorganisms, involved in enzymes controlling the nitrogen cycle and metabolic responses to oxidative stress. In this study, we examine the role of potential Ni utilisation by marine microorganisms in oceanic Ni and δ60Ni distributions, and specifically the influence of Ni-containing enzyme abundances on Ni isotope fractionation. Dissolved Ni concentrations and isotope compositions were measured together with microbial gene composition in Southern Ocean samples from the Antarctic Circumnavigation Expedition. We show that lower Ni concentrations are associated with higher δ60Ni values in surface waters north of the Sub-Antarctic Front compared to southerly locations. The high-latitude Mertz Glacier stands as an exception, as systematics between Ni and δ60Ni resemble those of low-latitude stations. No single enzyme could be identified as the sole driver of δ60Ni variations across all stations, as the strength and significance of correlations varied depending on the level of precision of functional annotations and the size fractions considered. Still, relative abundances of gene clusters annotated as urease and Ni superoxide dismutase (Ni-SOD) enzymes in metagenomes correlated with δ60Ni, suggesting the preferential removal of isotopically light Ni by microorganisms using these enzymes. Despite differences in enzymatic and taxonomic profiles, the three stations exhibiting heavy surface Ni isotope compositions share a specific nitrogen biogeochemistry, characterised by high particulate organic nitrogen pool and strong nitrate consumption. We thus hypothesise that Ni and δ60Ni distributions reflect variations in Ni metabolic requirements driven by complex microbial and enzymatic activity linked to the relative availability of inorganic and organic nitrogen. We further propose that the use of urea as an alternative nitrogen source during the late productive season could explain the unexpected isotope fractionation observed at Mertz. This study represents an initial exploration of the influence of enzymes and microbial communities on the Ni biogeochemical divide.
In recent decades, the population of the Eurasian beaver (Castor fiber) has undergone a rapid recovery from near extinction to abundance across large areas of Europe. The ability of this species to build dams of varying durability and extent has a significant impact on ecological processes, making beaver reintroduction an important environmental factor in recolonised areas. Although the effects of beaver dams on stream water chemistry have been studied extensively, general conclusions are often limited by site-specific conditions. Therefore, the aim of this study was to assess the impact of the flooding extent and age of beaver pond sequences on the physico-chemical properties of the water in and below beaver ponds compared to upstream channel sections across the seasons. The study was conducted on nine beaver-inhabited streams distributed across the Western Carpathians (Poland and Slovakia). The beaver ponds were divided into two types based on flooding extent: overflowing the river banks, or confined to the river channel (in-channel). Ponds were classified into three age categories: young (≤3 years old), moderate (4–9), and old (≥10). Water samples were collected above, within, and below the beaver pond sequences under baseflow conditions during four seasons in 2022–2023. The results showed that beaver dams have a strong impact on some physico-chemical stream water parameters during warm periods, when high temperatures accelerate biogeochemical processes. In particular, beaver ponds were associated with an increase in water temperature and decreases in dissolved oxygen, pH, NO3- and SO42- concentrations. The age of the beaver ponds had a more pronounced effect on water chemistry than the pond type. There was a greater decrease in dissolved oxygen and pH (throughout the study period) and SO42- concentrations (in spring and summer) in older ponds compared to younger ones. These changes might be regulated by the decomposition and aerobic/anaerobic oxidation of organic matter, which is more abundant in older ponds. Overall, the results suggest that seasonal conditions and pond age are important factors influencing the biogeochemical effects of beaver dams in mountain streams. However, most of the effects observed within the ponds were, to some extent, attenuated in downstream river sections.
Diatoms typically make a high contribution to carbon export (defined as more carbon exported relative to their production) in productive coastal and upwelling regions. However, oligotrophic subtropical gyres are vast but uniformly nutrient-poor, supporting only very low diatom abundances. This raises a critical question: can diatoms still achieve a high contribution to carbon export in such nutrient-limited regions, and if so, what factors enable this? Here, we integrated taxonomic, sediment trap, and metagenomic analyses at five stations in the western North Pacific Subtropical Gyre. Our observations reveal distinct niche partitioning: Navicula and Rhizosolenia tend to be enriched in the nutrient-depleted surface mixed layer, while Nitzschia, Chaetoceros, and Thalassiosira prevail in the deep chlorophyll maximum, reflecting hydrographic and nutrient influences on community assembly. Within our limited station coverage, measured intact cell fluxes ranged from 103 to 105 cells m−2 d−1, with estimated carbon fluxes of 0.11–313.03 µg C m−2 d−1. The total fluxes of diatom cells, biogenic silica, and carbon export were highest at Station K2b, which is influenced by the Kuroshio. At this station, the contribution of diatom export remained high, with the large, carbon-rich Rhizosolenia species dominating the sinking flux. Community assembly, characterized by functional traits such as cell size, carbon content, and fucose-containing sulfated polysaccharides (FCSPs) production, influences export composition and magnitude. Metagenomic analyses indicate a widespread capacity for degrading common diatom polysaccharides, but genes encoding the essential enzyme (GH107) for cleaving FCSPs are nearly absent across all stations. This deficit, together with the prevalence of FCSP-producing diatoms, suggests that biochemical resistance may assist carbon export. Our findings provide preliminary support that diatom community assemblages (shaped by hydrodynamics and nutrient supply) and microbial degradation resistance (via limited FCSP-targeting enzymes) modulate local heterogeneity in diatom export contribution. We conclude that predicting the biological pump's response to global change may require accounting not only for which diatoms are present, but also for which organic byproducts are protected from rapid remineralization. These results are based on a limited number of stations and a single season, and therefore warrant further testing.
Coastal waters contribute significantly to the total oceanic carbon uptake. In this context, the cumulative influence exerted by marginal seas may be conspicuous. However sparse and unevenly distributed observations in such regions pose a serious limit to an accurate, experimentally based quantification of carbon dynamics. The Southern Adriatic (SAd) is one of the key sites of the Mediterranean Sea where open-ocean deep water formation occurs, a process recognized as a major driver of carbon sequestration. However, observations in this region remained sparse, thus quantitative assessment of surface carbon dynamics and air-sea carbon flux are still limited. In this study, a recently validated, decade-long (2015–2024) high-resolution time series of surface partial pressure of CO2 (pCO2 sw) and hydrographic measurements collected at the EMSO-E2M3A South Adriatic observatory, located at the centre of the Southern Adriatic Pit, has been analysed. The results showed that seasonal temperature variability and winter vertical mixing were the dominant drivers of pCO2 sw variability, with biological processes likely contributing during the post-convective period. Air–sea CO2 flux (FCO2), derived from in situ observations, indicated a clear seasonal pattern, with the SAd acting as a CO2 sink during winter and as a source during summer. Importantly, the results revealed that the SAd acted as a weak-to-moderate annual carbon sink over the last decade. However, the magnitude of FCO2 was strongly influenced by the selected gas transfer velocity parametrization. Similarly, the use of a different wind speed input, for instance ERA5 reanalysis, also altered the estimated CO2 flux, highlighting the importance of carefully selecting wind products for regional air-sea FCO2 calculations. Finally, the results presented here showed how time series such as the SAd dataset can serve as critical assets for validating operational ocean models, such as the European Copernicus Marine Service for the Mediterranean, by helping to identify discrepancies in the simulation of key processes.
The aims of this work are: (i) To understand potential transformations and dynamics within the broad chromophoric dissolved organic matter (CDOM) pool in the sea surface microlayer (SML) and the underlying water (ULW) at a Mediterranean coastal site using high-resolution (biweekly, one-year) temporal data and by applying established absorbance indices across multiple spectral regions along with the novel fluorescent dissolved organic matter (FDOM) to CDOM, FDOM/CDOM index. (ii) To evaluate the relative contributions of in situ processes, upward flux from the ULW, and atmospheric (rainwater) inputs in the shaping of the dissolved organic matter (DOM) and CDOM pools in the SML. Twenty-two paired SML–ULW samples and fourteen rainwater samples were analyzed for dissolved organic carbon (DOC), UV–visible (250–700 nm) absorption spectra, and 3D fluorescence excitation emission matrices (EEMs). The SML was consistently enriched in DOC, CDOM, and FDOM relative to the ULW throughout the study. Enrichment factors (EFs) for long-wavelength absorption coefficients (a300, a370) exceeded 5 indicating a preferential accumulation of high molecular, aromatic absorbing DOM. Relationships between DOC, a300 and the spectral slope (S275−295) indicated that specific processes in the SML modulate the abundance and optical quality of DOM beyond bulk DOC quantity. Photodegradation was apparent in both layers, though more pronounced in the ULW. In the SML, photodegradation effects appeared to be partially counterbalanced by in situ production or aggregation of hydrophobic, optically active, higher-molecular-weight material. Parallel Factor Analysis (PARAFAC) identified four FDOM components: two humic-like (A–C, A–M) and two protein-like (T, B). Terrestrial humic-like (A–C) and tryptophan-like (T) fluorophores were dominant and strongly enriched in the SML (EF >4). However, humic-like and tryptophan-like components exhibited SML enrichment linked to both a300 absorption and layer, while tyrosine – like component was enriched independently of layer effects and mainly reflected a300 fluctuations. By introducing a new FDOM/CDOM index, a decoupling between fluorescent and non-fluorescent chromophoric organic fractions was revealed: the SML exhibited higher fluorescence in the UV-C/UV-B excitation regions (A, B, T peaks) but lower fluorescence in the UV-A/near-visible excitation region (C peak), suggesting selective accumulation of absorbing but non-fluorescent CDOM in longer wavelengths. Potential drivers of this decoupling include biological transformations, rapid microlayer reorganization, and atmospheric inputs. Rainwater showed DOC concentrations and absorption features comparable to the SML but distinct fluorescence characteristics. PARAFAC modeling of rainwater did not resolve the tryptophan-like fluorophore and revealed blue-shifted humic-like components, consistent with photochemically aged, low molecular weight DOM of mixed marine–terrestrial origin. Overall, the results indicate that wavelength-dependent enrichment of CDOM and FDOM in the SML is primarily driven by photodegradation, biological activity, rapid molecular reorganization, and atmospheric deposition, rather than upward DOM flux from the ULW.
Abstract. Biogeochemical and physical processes in the mesopelagic layer regulate long-term carbon storage in the ocean interior. However, uncertainties in particulate organic carbon (POC) budgets limit quantitative understanding of the biological carbon pump and its representation in models. Here we analyse POC budgets simulated by the NEMO4–PISCESv2_RC model in the upper 1000 m of the North Atlantic over a climatological seasonal cycle, evaluating model performance and diagnosing the mechanisms that regulate POC export and transfer efficiency. Comparison with satellite, Argo-float, shipboard, and sediment-trap data indicates generally realistic POC stocks and fluxes. However, the model exhibits systematic biases, including (i) excessive diatom dominance at mid–high latitudes, (ii) compensation between too-low primary production and excessive epipelagic export in the subtropics, and (iii) underestimated mesopelagic POC stocks at mid and low latitudes. In the model, the mesopelagic POC supply driven by gravitational export and large detritus increases poleward, while winter–spring mixing supplies an additional 37 % in the subpolar region. Up to 60 % of mesopelagic POC supply is intercepted by zooplankton, yet most is recycled to detritus through fragmentation and trophic processing. This detrital loop modulates particle size, sinking speed, and degradation pathways, and is seasonally reinforced at mid–high latitudes. The lability of exported POC increases with latitude, whereas temperature-driven decay rates decrease with latitude. These opposing gradients result in maximal mesopelagic POC flux attenuation at midlatitudes, coincident with peak productivity. Small detritus plays a central role in the model, accounting for ∼ 55 % of mesopelagic POC decay and driving 33 %–50 % of vertical flux at 1000 m. These large modelled contributions reflect substantial biological supply and a pronounced vertical decline in lability, together favouring mesopelagic transfer of small POC. We propose POC budget analysis as a mechanistic framework for identifying structural biases and constraining inter-model spread in projections of the biological particulate carbon pump.
Oceanic dissolved oxygen concentrations are thought to be declining under ongoing global warming, yet their variability remains less well understood than that of physical parameters such as temperature and salinity, primarily due to the limited spatial and temporal coverage of oxygen observation. Here, we examine linear trends in potential temperature, salinity, and dissolved oxygen in the North Pacific over the past two decades (2004-2023), using the GOBAI-O2-v2.2 dataset (Version 4.4). We compare the diagnosed oxygen trends with those of physical parameters to reveal the spatial structure of recent changes. The oxygen trends inferred from GOBAI-O2 are broadly consistent with trends observed along ship-based hydrographic repeat lines. While basin-scale deoxygenation is evident, we also identify localized oxygen increases on specific density surfaces. By relating these patterns to the surrounding physical environment, we find that the spatial heterogeneity in oxygen trends is consistent with known oceanographic processes, including the southward retreat of the oxygen minimum layer and the northward migration of a front separating the subtropical and subarctic gyres. These results underscore the value of GOBAI-O2 data in linking physical variability to previously unrecognized biological and biogeochemical patterns in the ocean.
Negative CO2 emission technologies such as ocean alkalinity enhancement, in tandem with emissions reduction are necessary to keep the climate system below a critical tipping point. While the biogeochemical consequences of alkalinity enhancement remain poorly constrained, field deployment is accelerating in the commercial sector, leaving questions of ecosystem impact in the wake. In this study we conduct alkalinity perturbation experiments to capture the resultant impact to the organic carbon and calcium carbonate pools. We quantify shifts in dissolved/particulate inorganic and organic carbon after the addition of three alkalinity sources – NaOH, CaO, and CaCl2 + NaHCO3 (to simulate accelerated weathering of limestone). These experiments are conducted with coastal sea water with enhancements of ∼ 500 and ∼ 1000 µmol kg−1 alkalinity, and incubated in situ, to elucidate the impact over 0–4 d. 13C isotope spikes were added to trace carbon partitioning throughout the experiment, and a few bottle experiments were completely isolated from the light via bottle shading to assess impacts on non-photosynthesizers. Despite a wide range in the initial ambient particulate carbon (both organic and inorganic) there was no statistically significant calcium carbonate precipitation or change in the organic carbon partitioning after a perturbation of ∼ 500 µmol kg−1 alkalinity in the form of NaOH, CaO or CaCl2 + NaHCO3. An increase of alkalinity by ∼ 1000 µmol kg−1 after CaO addition resulted in a statistically significant decrease of particulate organic carbon and dissolved oxygen relative to the control. To understand how a decrease in the particulate organic carbon may impact downstream trophic transfers, future studies should resolve the observed changes in particulate organic carbon by characterizing biomass within various particle class sizes with further filtration, microscopy, flow cytometry, and `omics analyses.
Tropical peatlands, compared to their boreal counterparts, are vastly understudied despite acting as a significant terrestrial carbon sink, sequestering 100—300 Gt of carbon. In particular, the low number of field-based studies from Latin America and the Caribbean limits our knowledge of these important wetland ecosystems. Across the tropical Panamerican region, peatland location, soil characteristics, inception ages, and carbon accumulation histories remain largely unknown. These datasets are needed to inform a mechanistic understanding of why peat develops in certain areas but not in others, both in terms of peat initiation conditions as well as the factors that enable peat to subsist over centuries and millennia. Here we present extensive, high-resolution laboratory datasets from 11 peat cores from 4 peatland types from Costa Rica (high-elevation, riverine, coastal palm swamp, and mangrove). A multi-proxy palaeoecological approach was employed to shed light on the successional pathways and past conditions that have allowed these peatlands to form, as well as to provide a first estimate of their carbon stock. The core characterization includes radiocarbon dating, loss-on-ignition, carbon and nitrogen content, and plant macrofossils. Fourier transform infrared spectroscopy (FTIR) was also used to assess changes in organic matter quality across sites and over time. The averaged peatland carbon stock in Costa Rica is estimated at 1080 MgC ha−1, making these ecosystems exceptionally rich carbon stores that are comparable to values found in lowland Amazonian peatlands. Overall, this research provides a basis for understanding long-term carbon accumulation within Caribbean tropical peatlands.
Hemiboreal forests bridge boreal and temperate biomes by combining functional and compositional features of both and playing a key role in regional carbon and water cycling. Water (WUE), carbon (CUE), and light (LUE) use efficiencies provide integrative indicators of how effectively ecosystems convert available resources into carbon uptake, yet their long-term dynamics and controlling factors remain poorly explained in hemiboreal forests. We analysed nine consecutive growing seasons (2016–2024) of eddy covariance measurements from an old upland hemiboreal coniferous forest in southern Estonia to quantify WUE, CUE, and LUE and to identify their controls at daily and growing-season scales and along a standardized precipitation-evapotranspiration index (SPEI) defined hydroclimatic gradient. Growing-season air temperature and vapour pressure deficit (VPD) increased over the study period. Despite this trend, WUE remained generally stable across years, with only one deviating growing season (2022) linked to intensified carbon uptake over a shorter season length. In contrast, CUE exhibited pronounced variability among growing seasons, driven primarily by changes in net ecosystem production and respiration dynamics. LUE was remarkably stable and showed no indication of age-related decline. At the daily scale, VPD controlled WUE and LUE, whereas photosynthetically active radiation exerted dominant control over CUE. Along the hydrometeorological gradient, all three resource use efficiencies responded non-linearly, but WUE and LUE remained generally stable, while CUE was the most variable metric and reflected shifts in the balance between carbon uptake and respiratory losses. Together, these results reveal differentiated sensitivities of ecosystem efficiencies to atmospheric drying and identify CUE as the most responsive indicator of hydroclimatic variability. Our findings provide new insight into the functional stability and potential thresholds of hemiboreal coniferous forests undergoing climate change.
Peatlands are critical components of the global carbon (C) cycle, storing large amounts of soil organic carbon (SOC). However, drainage substantially alters their carbon exchange and hydrological functioning, often converting them into net carbon dioxide (CO2) sources. This study presents the first year-round, ecosystem-scale Eddy Covariance (EC) assessment of CO2 dynamics from an unmanaged drained peatland in western Iceland, originally drained in the early 1960s. Two years of continuous EC measurements were collected alongside high-resolution environmental data, including solar radiation, air and soil temperatures, soil water content, and groundwater level. Several multispectral drone flights were also conducted during the study period, which provided seasonal NDVI-based estimates of canopy greenness. The two study years differed markedly in annual weather during the growing season (GS), with 2023 GS being unusually warm and dry, while 2024 GS was cold and wet. Despite these contrasts, annual net ecosystem exchange (NEE) remained similar between the 2 years. The annual NEE was dominated by non-growing-season (NGS) respiration, which highlighted the necessity for year-round measurements. Overall, the site remained a persistent CO2 source, emitting 4.1-4.4 tCO2-Cha-1yr-1 nearly 60 years after drainage. Temperature exerted the strongest control on ecosystem respiration (Reco), while gross primary production (GPP) responded primarily to seasonal irradiance and NDVI. A compensatory mechanism was observed during the warm year (2023) at this relatively cool site, where warming-induced increases in Reco were offset by an enhanced GPP, resulting in a relatively stable annual NEE despite meteorological contrasts. Soil moisture and vapor pressure deficit played only minor roles under these cool and moist conditions. These findings highlight the need for continued monitoring of unmanaged drained peatlands to better quantify their contribution to regional greenhouse gas budgets.
Abstract. Peatland drying is an important process affecting greenhouse gas (GHG) emissions. Ditching of peat for drainage to plant forest has been a widespread management practice in the Nordic countries, and drying increasingly occurs also from climate change induced drought. Previously published meta-analyses from literature suggest that drainage increases soil CO2 emissions by enhancing oxic decomposition in aerated upper layers while suppressing CH4 emissions. However, these data do not elucidate short-term variations of GHG fluxes during drainage and usually only regress GHG emissions as a function of the annual mean water table. Here we developed a new parameterization of peat drainage in a land surface model that represents peat processes and fluxes of CO2 and CH4, by adding a machine-learning module to predict the daily water table depths from simulated soil moisture in the upper soil layers and a ditch that receives drainage water. Because peatland pre-drainage GHG emissions vary between sites and influence subsequent changes following drainage, idealized simulations were performed for virtual drainage applied to a collection of 10 pristine sites, where the model parameters are calibrated against observed GHG fluxes. Different drainage intensities are simulated by prescribing lower water table depths from setting the ditch depth from 5–80 cm below the initial water surface. The resulting GHG flux changes across sites are compared with meta-analysis data from northern sites and show realistic results with a reduced CO2 sink and reduced CH4 emissions. Additional comparison with continuous flux data collected in the UK for different sites associated with increasing drainage levels also shows good model performance. Overall, using GWP100 to compare the effect of CH4 vs. CO2 flux changes, our model simulations suggest only small net GHG emission changes in CO2-equivalent GHG emissions under drainage scenarios over multi-decadal timescales, yet with differences between sites. Over time, simulated emission factors of CO2 flux decrease because of exhaustion of labile soil organic substrate for decomposition, while reductions in CH4 emissions are amplified due to decreased availability of material for anoxic decomposition. The sensitivities of CO2 flux changes to increased water table depth changes are primarily controlled by initial CO2 and CH4 fluxes, initial soil carbon content, peat vegetation community, air temperature and initial water table depth. The influence of peat vegetation on the GHG flux sensitivities in the model occurs via differing lability of soil organic carbon pools, with moss-dominated sites having a lower sensitivity due to their longer peat turnover time. Nonetheless, our calibrated global model remains limited in its ability to mechanistically represent drained peatland systems, particularly regarding extrapolation and representation of dynamic soil and hydrological processes. Our model-simulated sensitivities of GHG fluxes to drainage can be approximated by linear regressions using site-level variables, which, despite the limitations, may offer a simplified, exploratory tool for estimating drainage effects.
The task of reliably partitioning evapotranspiration (ET) is imperative so that we can better understand how individual components of the terrestrial water flux are contributing to the global hydrological cycle and changing under a warming climate. By constraining how evaporation (E) and transpiration (T) separately adapt to increased global temperatures, we can make more accurate predictions in land surface models, further our understanding of plant water use, and better manage our limited water resources. Eddy covariance (EC) is a globally used technique that measures net biosphere-atmosphere fluxes, including ET, and if reliably partitioned, presents a promising way to constrain E and T values and trends across ecosystems. Several EC-based ET partitioning methods exist, and there is a need for an updated comprehensive guide to the available approaches. This systematic literature review was conducted with the objectives of (1) identifying EC-based ET partitioning methods and categorizing them based on underlying ecosystem assumptions, (2) determining the main advantages and disadvantages of each method dependent on their assumptions and data requirements, and (3) evaluating how broadly these methods have been applied based on geographic location and ecosystem type. The review identified 11 independent partitioning methods applied across 129 studies. Methods using assumptions of underlying water use efficiency (uWUE) and ecosystem conductance all use the relationship between ET and gross primary production with vapor pressure deficit (VPD) to estimate the transpiration ratio (T / ET). Additionally, two machine learning based methods, one method assuming a linear relationship between ET and gross ecosystem photosynthesis, and four methods using high frequency EC data to estimate T / ET were identified. The uWUE methods, while the most frequently used partitioning approach, consistently predicted the lowest T / ET estimates when compared to both other EC and many non-EC based partitioning methods. The machine learning methods predicted the highest T / ET values compared to other EC-based methods which agreed well with values estimated with independent methods. Savannas and evergreen broadleaf forests had the highest T / ET of all ecosystem types while deserts and wetlands had the lowest. Leaf area index and soil water content were found to be the most important drivers of T / ET values and trends with VPD and air temperature also displaying significant effects. Of the global studies identified in this review, an average annual T / ET value of 0.573 ± 0.10 was found, a value that falls within the range of other studies using isotopic partitioning, remote sensing methods, and global estimates from various ecosystem models. More testing, specifically increased paired analyses of two or more EC-based ET partitioning methods on the same dataset and more validations against independent observations, are needed in order to fully understand the applicability of each method, their differences, and to better constrain global T / ET dynamics.
Hydrological extremes are continuing to intensify under climate change. However, the responses of vegetation to dry and wet soil moisture extremes, and the dominant mechanisms of these responses, have not yet been analysed consistently. In this study, we utilized long-term observations of Normalized Difference Vegetation Index (NDVI) as a proxy of vegetation responses to soil moisture extremes. We then analysed related predictors with a machine-learning attribution approach to assess the role of pre-extreme vegetation conditions, characteristics of extremes, and of the environmental background. Vegetation generally loses greenness during dry extremes, indicated by widespread and consistent negative NDVI anomalies. This is mainly modulated by the characteristics of the extreme (especially seasonal timing) and pre-extreme vegetation conditions, which reflect varying vegetation vulnerability. In contrast, wet extremes lead to more heterogeneous responses, including both positive and negative NDVI anomalies. Negative vegetation responses during wet extremes are most consistently associated with pre-extreme vegetation conditions, while environmental background variables such as climate (e.g., long-term mean air temperature, aridity) and topographic variability show comparatively stronger relevance than for dry extremes. Extreme characteristics also contribute substantially, though with greater regional variability than for dry extremes. This illustrates that vegetation response to wet extremes is complex and potentially influenced by different processes. Further, vegetation stress can occur even under relatively less severe extremes when responses are strongly modulated by environmental background conditions, indicating localized vulnerability arising from adverse climatic, soil, or topographic conditions. These results highlight the roles of seasonal timing and of environmental background conditions for impacts of soil moisture extremes on vegetation. This clarifies the predictability of ecosystem responses to hydrological extremes and serves as a basis for related management planning.
Pristine peatlands function as natural carbon dioxide (CO2) sinks, but anthropogenic drainage turns them into sources of CO2, responsible for 2 %–5 % of global annual greenhouse gas (GHG) emissions. Complex interactions between vegetation, soil, climate, and hydrology produce highly variable CO2 budgets on different types of peatlands and between years. Abandoned drained peatlands are considered low-hanging fruits for rewetting due to expected high GHG emissions and low resistance to repurposing yet remain underrepresented in research. To close this gap in the literature, we measured 3 years (2023–2025) of CO2 and methane (CH4) fluxes alongside meteorological and hydrological conditions in a drained shrub-dominated ombrotrophic raised bog in northwest Germany, investigating carbon flux budgets and the main seasonal drivers of fluxes. Methane fluxes were negligible throughout, likely due to water tables consistently deeper than 15 cm. Annual CO2 budgets were highly variable: the site was a considerable source of CO2 in 2023 and 2025 (112.6 ± 14 and 47.6 ± 27.8 gCm-2a-1) but a weak sink (−24.8 ± 15.1 g C m−2) in 2024. An anomalously warm spring in 2024 triggered an earlier onset of CO2 uptake and increased maximum CO2 uptake capacity from April to June. In contrast, warming later in the growing season increased CO2 emissions due to a stronger reaction of respiration than of photosynthesis to warming – highlighting how the timing of climate anomalies matters. Partitioning the effects of high air temperature (TA) and vapor pressure deficit (VPD) revealed that high VPD suppressed carbon fluxes in the first half of the growing season but not the second, while extreme TA did not limit gross primary production (GPP) or ecosystem respiration the way extreme VPD did. TA and solar radiation were the dominant daily flux drivers; water tables had marginal effects on daily or interannual carbon flux variability. Together, our results demonstrate that the timing of TA and VPD anomalies – mediated through vegetation responses – decisively shapes their impact on the carbon balance. These results will become increasingly relevant as climate extremes intensify with ongoing global warming.
Global riverine particulate organic carbon (POC) fluxes have declined worldwide due to dam-induced reductions in sediment load. However, how the composition of riverine POC has evolved in response to declining sediment supply, and how such shifts influence OC burial in subaqueous deltaic systems remain unclear. Here, we collected suspended particulate matter (SPM) from the Changjiang Estuary in summer and winter 2025 to analyze N / C molar ratios and δ13C values. These data were integrated with a four-decade (1980–2021) dataset comprising OC proxies (N / C molar ratios, δ13C and Δ14C) for SPM in the Changjiang Estuary and surface sediments from the Changjiang subaqueous delta. Our results reveal a temporal increase in N / C molar ratios and a decrease in δ13C values in riverine SPM. Based on a Bayesian end-member mixing model, we attribute these trends to an increasing proportion of POC derived from freshwater algae and a decreasing proportion of POC originating from soil/bedrock erosion. This temporal increase in river-delivered labile algae POC drove a decrease in OC preservation efficiency in the Changjiang subaqueous delta from 15.1 % (before 2003) to 10.7 % (after 2003), resulting in a pronounced reduction in deltaic OC burial. Consequently, the amount of OC retained in sediments decreased by approximately 50 %, from 68 kt per month in 2001 to an average of 34 kt per month during the flood seasons of 2011–2020. Our findings emphasize that the shifts in riverine OC sources, not merely the decline in total OC flux, may exert great effects on OC burial in deltaic systems globally.
Vegetated roofs (i.e. green roofs, GRs) have been emerging as a promising nature-based solution in urban environments to mitigate climate change impacts, such as heat waves, urban flooding, and increased greenhouse gas emissions. Green roofs were shown to provide various ecosystem services, such as carbon sequestration from the urban atmosphere. The present study leverages a 9-year, long-term time series of continuous, integrated flux measurements on a large, extensive GR in Berlin, Germany, using the eddy-covariance technique. We investigate, (1) whether the GR is a net annual sink for carbon, (2) if the sink intensity remains stable over the whole study period, and (3) the coupling between carbon, water, and energy fluxes at different temporal scales to determine their role in shaping the net ecosystem exchange (NEE) of the GR ecosystem. The extensive GR was a moderate carbon sink with an average annual NEE of −92, ranging from −154 to +8 g C m−2 in the study period from 2015–2023. In the final two years, 2022 and 2023, the annual NEE shifted toward net carbon release, coinciding with an abrupt increase in substrate organic carbon, which has been linked to external input of carbon to the GR system. During the study period, the roof retained 51 % of precipitation, with a strong coupling between soil moisture, evapotranspiration, sensible heat flux, and carbon flux. Low substrate water content (<≈0.05 m3 m−3) reduced evaporative cooling and suppressed carbon uptake during the summer. The findings demonstrate the importance of integrated flux monitoring and emphasise the multifaceted environmental benefits of extensive GRs while also pointing to their structural constraints.
