Earlier efforts to assess anthropogenic impacts on river greenhouse gas (GHG) emissions mainly relied on local-scale data, overlooking how cross-boundary factors such as climate, topography, socio-economic and demographic context shape river pollution and GHG emissions. To better understand the influence of urbanization and agriculture on riverine GHG fluxes, we measured fluxes at 156 sites across four river basins and continents. We linked land use and demographic contexts to river biogeochemistry via the human footprint methodology and explainable machine learning. Rivers crossing densely populated areas became CH4 hotspots when waste generation outpaced treatment capacity, as untreated effluents and flow-controlled urban channels, increased residence times and promoted anoxic conditions conducive to methanogenesis. These rivers emitted two times more than other land use classes and up to 200 times more than urban sites with adequate infrastructure. Cropland sites exhibited the highest CO2 and N2O fluxes, which were double those from urban sites, driven by agricultural practices promoting lateral transport delivering both substrates (nutrients and organic matter) and dissolved GHGs to rivers. These results demonstrate that pollution from human activities, rather than river size or Strahler order, is the dominant control on river GHG fluxes. Accordingly, improving land and wastewater management to reduce pollutants entering rivers could significantly mitigate elevated riverine GHG emissions.

Archives of observed weather data present unique opportunities for scientists to obtain long time series of the historical climate for many regions of the world. Unfortunately, most of these observational records are to-date available only on paper, and thus require digitization and transcription to facilitate analysis of climatic trends. Here we present a new open-source software, MeteoSaver, that uses machine learning (ML) algorithms to transcribe handwritten records of historical weather data. MeteoSaver version 1.0 processes images of tabular sheets alongside user-defined configuration settings, performing transcription through five sequential steps: (i) image pre-processing, (ii) table and cell detection, (iii) transcription, (iv) quality assessment and quality control, and (v) data formatting and upload. As an illustration and evaluation of the software, we apply MeteoSaver to ten pictured sheets of handwritten temperature and precipitation observations from the Democratic Republic of the Congo. The results show that 95 %-100 % of the daily temperature values can be transcribed, of which a median of 74.4 % reached the highest internal quality flag and 74 % matches with the manually transcribed record, yielding a median mean absolute error of 0.3 degrees C. These results illustrate that MeteoSaver can be applied to a range of handwriting styles and varying tabular dimensions, paper sizes, and maintenance conditions, highlighting its potential for transcribing tabular meteorological observations from multiple regions, especially if the sheets have a consistent format. Overall, our open-source software can help address the challenges of limited available hydroclimatic data within many regions of the world, by helping to save millions of handwritten records of historical weather data presently stored in archives, and expedite research on the climate and environmental changes in data scarce regions.

Despite their increasing recognition in global greenhouse gas (GHG) budgets, riverine emission estimates face challenges from data gaps and methodological inconsistencies. To evaluate these challenges, this study reviewed 568 publications on riverine emissions published from 2011 to 2024. We analyzed monitoring methods, influencing variables, data characteristics, and emission pathways, using PRISMA protocol. River research represents only 8 % of all aquatic GHG studies, with a strong geographical bias toward large rivers, especially in Asia (52 %). Small rivers remain underrepresented despite their potentially substantial contributions. Current monitoring approaches are dominated by small-scale methods (floating chambers: ∼30 %; headspace method: ∼50 %) that are accurate yet have poor spatiotemporal representation. Large-scale methods utilizing remote sensing and unmanned platforms comprise less than 5 % of applications, leaving critical gaps in regional-scale assessments. Most studies (64 %) span less than one year with low-frequency sampling (39 % one-time snapshots), limiting comprehensive understanding of temporal dynamics. Researchers have focused primarily on instream variables that directly affect local GHG production (90 %), while basin-scale factors have received less attention. We propose a decision tree framework for selecting optimal methods based on spatiotemporal scales, available resources, and emission pathways. Future monitoring approach should integrate small- and large-scale measurements to combine accuracy with broader coverage. Furthermore, isotope and molecular analyses, underutilized in 85 % of studies, can clarify underlying biogeochemical processes and microbial activities. Their integration will thereby reduce uncertainties in global riverine GHG inventories and support more effective mitigation strategies.

Tropical forests contribute disproportionately to global carbon cycling, yet their resilience under climate warming remains uncertain, partly due to limited understanding of leaf-level temperature responses of photosynthesis. In particular, the role of fine-scale canopy microclimate in shaping photosynthetic temperature responses in tropical trees has been overlooked. We quantified vertical microclimate variation and measured leaf-level photosynthetic temperature responses in 13 coexisting evergreen tree species spanning the full canopy profile in a lowland Congo Basin forest. Leaf gas exchange measurements were integrated with structural leaf traits and high-resolution microclimate profiles to assess how temperature conditions and ecological strategies shape photosynthetic responses. Photosynthetic traits, including the light-saturated photosynthetic rate at the temperature optimum and stomatal conductance at the temperature optimum, increased with canopy height, with pioneer species showing steeper increases than non-pioneers. The temperature optimum of photosynthesis (Topt) was positively related to both mean and maximum leaf temperature (Tleaf), driven mainly by interspecific differences rather than intraspecific plasticity. This suggests that Topt reflects species-level adaptation to the temperature conditions of their canopy niche rather than leaf-level adjustment to local microclimate. Stomatal conductance influenced Tleaf via transpiration and thereby contributed to shaping Topt. Leaves experiencing larger temperature fluctuations showed reduced sensitivity, reflected in a broader photosynthetic temperature-response width (Ω). Ω was also positively associated with structural traits such as leaf mass per area and leaf dry matter content, both within and among species, indicating that greater structural investment helps sustain higher photosynthetic rates across wider temperature ranges and enhances tolerance to temperature variability. By linking canopy microclimate, physiological traits, and structural characteristics, our findings demonstrate how vertical microclimatic gradients and functional diversity jointly determine photosynthetic temperature responses in tropical forest trees. Incorporating leaf-level temperature regimes, stomatal regulation, and trait variation into vegetation models could improve predictions of tropical forest carbon dynamics under climate change.

BACKGROUND AND AIMS:Understanding spatiotemporal variation in plant functional traits and intrinsic water use efficiency (iWUE) is essential to evaluate how plants respond to environmental change. In forests of the Congo Basin, we examined spatial and century-scale temporal trends in the morphological and physiological characteristics of the leaves of Coffea canephora, a widespread understorey species from West Africa to the African rift (Uganda). METHODS:Using 179 herbarium samples collected during two periods (1900-60 and 2016-21), we measured the specific leaf area (SLA), stomatal size (S), stomatal pore size (SPS), stomatal density (SD) and maximum diffusive stomatal conductance to CO2 (gcmax). Stable carbon and oxygen isotope ratios (δ13C, δ18O) were measured from leaf cellulose to infer variation in photosynthetic activity iWUE. KEY RESULTS:We found a significant spatiotemporal variation in leaf morphological and physiological traits and iWUE. δ13C ranged from -34.84 to -24.11 ‰, and δ18O from +26.96 to +34.16 ‰. Over the past century, SLA and S increased, whereas SPS, SD, gcmax, δ13C and iWUE decreased. Spatially, morphological traits appeared shaped by long-term environmental adaptation, while physiological traits responded more to short-term drivers such as atmospheric CO2 and precipitation, highlighting a functional decoupling that may limit photosynthetic performance of C. canephora under future climate change. The trait correlations showed coordinated functional trade-offs: SLA was negatively correlated with iWUE, while S, SD and gcmax were positively associated, reflecting trade-offs between carbon gain and water conservation. CONCLUSIONS:Our study underscores the value of herbarium-based multitrait approaches in reconstructing long-term plant responses and their relevance for understanding climate sensitivity in tropical understorey species.

Abstract The Congo Basin, spanning over 3.7 million km 2 across Central Africa, plays a critical role in regulating global climate, sustaining biodiversity, and supporting regional livelihoods. We explore the ecological functions of the Congo Basin ecosystems, emphasizing their role in the carbon cycle. We synthesize current knowledge on biogeochemical processes, carbon stocks, species interactions, and biodiversity patterns, while highlighting key data gaps and research needs. The region’s forests, soils, wetlands, and aquatic systems together form one of the world’s most significant carbon sinks, with unique characteristics, including high megafaunal density, extensive peatlands, and relatively low deforestation rates, shaping its contributions to carbon sequestration and climate regulation. We detail carbon cycle dynamics across lowland, montane, flooded, and savanna ecosystems and underscore the vast belowground carbon storage in the Cuvette Centrale peatlands. Patterns of alpha and beta tree species diversity affect ecosystem function and resilience, with plant functional traits playing a key role in nutrient cycling and productivity. Species such as forest elephants influence forest structure and carbon storage through seed dispersal and disturbance. Moreover, strong land-atmosphere feedbacks mean that evapotranspiration from the Congo Basin’s tropical forests plays a key role in shaping regional rainfall patterns. Land use and climate change pose growing threats to these functions, potentially triggering regime shifts and biodiversity loss. Ultimately, the Congo Basin remains underrepresented in ecological research and monitoring despite its global importance. Enhanced field-based and remote sensing efforts are urgently needed to inform integrated conservation and climate change mitigation strategies that account for both carbon dynamics and biodiversity.

The Congo Basin in Central Africa remains one of the few regions globally where the Intergovernmental Panel on Climate Change (IPCC) has not reported observed trends in hot extremes or attributed such changes to anthropogenic influences, primarily due to the scarcity of in situ observational data. Similarly, observed changes in extreme daily precipitation since the 1950s have not been assessed for this region. Although extensive daily weather records exist, spanning from the 1900s to the early 2000s and covering numerous stations across the basin, the majority of these remain archived on paper, limiting their accessibility for climate analysis. Here, we present our historical weather data rescue project entailing archived data from 37 weather stations in the Democratic Republic of the Congo (DRC). We outline the digitization process of these archival records, comprising over 1 million individual observations, and describe the subsequent transcription using MeteoSaver version 1.1. From these records, we construct daily time series of daily maximum, minimum, and average temperatures, precipitation, as well as dry bulb and wet bulb temperatures measured at three times per day (06:00, 15:00, and 18:00). This newly transcribed dataset provides a critical foundation for undertaking hydroclimatic trend analysis in the Congo Basin, one of the world’s most data-scarce yet climatically significant regions. Using this data, we conduct an analysis of multi-decadal temperature trends across the basin. Our findings reveal a consistent and accelerating warming signal since the 1960s, characterized by a rightward shift in the distribution of daily maximum, minimum, and average temperatures with each successive decade. Median trends across the stations are 0.24°C, 0.09°C, and 0.18°C per decade for daily maximum, minimum, and average temperatures, respectively, corresponding to approximately 0.7°C, 0.3°C, and 0.6°C of warming over 30 years. We further find an increasing frequency of hot extremes and a decreasing frequency of cold events with each successive decade during the period 1960-1990, across the aggregated station data. Specifically, the most recent decade exhibits approximately twice as many hot days per year and about half as many cold days compared to the earliest decade. Overall, this analysis of newly digitized historical weather data for the DRC highlights the urgent need to close the knowledge gap on climate trends in the Congo Basin.

The Congo Basin and its contiguous forests harbor globally significant carbon stocks, estimated at 65 gigatons of C (GtC) above and belowground. Despite rising temperatures and intensifying droughts, they have remained a carbon sink, albeit weak: 0.26-0.50 GtC yr.-1 carbon uptake since 1980. However, these forests' carbon stocks and fluxes, including gross primary productivity, respiration, net primary productivity, and riverine carbon transport, remain poorly quantified. This limits understanding of the region's role in the global carbon cycle, its vulnerability to environmental change, and its potential as a long-term carbon sink. We review and quantify Congo Basin and contiguous forest carbon stocks and fluxes and synthesize the current knowledge on how key global change drivers shape the region's carbon cycle. We find limited responses to long-term precipitation variability, but declining stocks and fluxes in response to long-term and increasing temperature and drought frequency. Land cover and land use changes, largely driven by small-scale agriculture, logging, and agro-industrial expansion, reduce carbon stocks, ecosystem structure and functioning, and animal-mediated ecosystem services. In contrast, large-scale savanna biomass burning delivers phosphorus and nitrogen to Congo Basin forests via cross-equatorial winds, providing additional nutrients and supporting carbon sequestration. In situ studies suggest that CO2 fertilization has increased intrinsic water-use efficiency, although its effects may be modulated by climate change, and its impacts on biomass accumulation remain uncertain. Legacy effects from historical land use and climate change likely shaped present-day vegetation structure, yet their relative influence is unclear. High-resolution carbon monitoring, improved remote sensing, and strengthened in situ measurement networks are needed to quantify the impacts of these key drivers and their interactions on the Central African carbon cycle. This is needed to inform conservation strategies and advance understanding of the region's future as a carbon sink under global change pressures.

Primer bias in 16S rRNA gene amplicon sequencing can distort microbial diversity estimates by underrepresenting key taxa. We introduce a modified primer pair (V4-EXT) targeting the hypervariable V4 region of bacterial and archaeal 16S rRNA genes, with improved in silico taxonomic inclusivity. To benchmark performance, we analyzed 938 samples from terrestrial, aquatic, and host-associated habitats, comparing microbial community profiles derived with V4-EXT and the currently most widely used V4-targeted primers. V4-EXT substantially improved the detection of Patescibacteria and other underrepresented lineages, such as Chloroflexi and Iainarchaeota, while enhancing recovery of novel amplicon sequence variants across sample types. Overall, V4-EXT provides broader taxonomic coverage and more inclusive microbial community profiles, particularly in high-diversity ecosystems such as groundwater and soils. We propose V4-EXT as a robust successor for comprehensive microbial community analysis across diverse habitats.

Atmospheric deposition is a critical driver of biogeochemical cycling in forest ecosystems. Among the pathways of deposition, throughfall (TF) — precipitation that has interacted with the forest canopy — plays a significant role in the input of atmospheric substances and canopy leachates to the forest floor. We investigated the influence of airborne pollen deposited in TF on its chemical composition across 60 Level II plots of the ICP Forests network in eight European countries. Based on 196 TF samples collected during the 2018 early vegetative season, we identified 53 pollen taxa, with Pinus, Picea, Fagus, and Quercus accounting for 91.4

While the introduction of the Neolithic way of life in central Belgium around 5300 BCE is well-documented, the provenance and mobility patterns of Middle to Final Neolithic groups in southern Belgium (Wallonia) remain unclear. This work presents the first multi-element isotopic (strontium, 87Sr/86Sr; oxygen, δ18O; carbon, δ13C) data from prehistoric human dental enamel from the region. The study includes a total of 29 individuals, coming from karstic caves in the Meuse basin, the mining complex of Spiennes, and the megalithic tomb of Wéris II. The study also explores the variability of bioavailable strontium ratios in the geologically heterogeneous Meuse basin using modern plants. The analysis of multi-element isotopic data reveals high δ18O values and diverse 87Sr/86Sr ratios. The findings suggest that these individuals likely originated from or spent their childhood in present-day Belgium. Furthermore, the study highlights limited mobility during the Final Neolithic period, characterized by a combination of local residency and potential short-distance mobility or post-mortem movements. Overall, this study provides the first δ18O values from ancient human remains in the region and reshapes our understanding of human mobility during the Neolithic in present-day Belgium.

Carbon (C) uptake in regrowing secondary forests increasingly dominates landscape-scale C dynamics in the tropics. Understanding the recovery trajectories of net primary productivity (NPP) and C allocation, along with the underlying demographic and functional drivers of biomass recovery, is therefore critical. Using a space-for-time setup spanning five successional stages, we showed that - for forests in the Yoko reserve, in central Africa - C fluxes related to recruitment and mortality decreased along succession, alongside a gradual transition from a forest with high stem density and acquisitive species to one with lower stem density and more conservative species. In the first decade of succession, NPP allocation shifted from being dominated by woody productivity to canopy productivity. Higher tree mortality in early succession counterbalanced the higher woody NPP, producing a relatively constant net woody C sink along succession. While being positive, this woody C sink was small, suggesting a slow but steady recovery to old-growth aboveground C stocks ranging between 171 and 238 Mg C ha-1. Overall, our findings demonstrate the potential of secondary forests in the Congo basin to mitigate climate change, but also emphasize the need to conserve old-growth forest C stocks and expand long-term observational data to better constrain regional C recovery dynamics.

Sediment pollution in (sub)tropical rivers and lakes of Queensland and East Africa is rapidly increasing, largely driven by subsurface erosion of deep alluvial and volcanic soils. These regions experience strong rainfall variability and flooding linked to climate and topographic controls, resulting in highly episodic soil loss and sediment transport. However, monitoring sediment sources during extreme events in remote (sub)tropical catchments remains challenging, meaning current understanding is often based on low temporal resolution data or visually dominant erosion features. In addition, the current set of sediment tracing approaches struggle to discriminate sources in deep tropical and alluvial soils or behave non-conservative in these environments.This study addresses these methodological limitations to improve quantification of dominant sediment sources and soil loss processes in (sub)tropical catchments. We combine multiple water and suspended sediment monitoring tools, including low-cost automatic samplers, to capture the fluxes and variability of suspended sediment. We subsequently developed a novel sediment fingerprinting approach based on sequential extraction of elemental soil fractions. This tracer framework enables discrimination not only between catchment zones but also among multiple subsurface soil layers in deep alluvial and volcanic profiles. The tracer data are integrated into mixing models and event-scale sediment hysteresis analyses to construct dynamic sediment budgets and capture non-linear sediment responses to extreme rainfall.Our results reveal the critical role of downwearing and chemical dissolution processes in large alluvial gullies of northern Queensland. These processes are largely neglected in current catchment models and gully analyses because they are not evident from repeat imagery assessments of gullies that demonstrate headcut retreat and bank collapse. In the Albert River (Southeast Queensland), we show that flooding associated with tropical Cyclone Alfred contributed approximately 60% of annual sediment export, dominated by erosion of subsurface soils from recent urban developments. This contrasts with earlier assessments in which radionuclide tracers provided only a binary subsurface signal, which together with visually evident bank collapse from aerial imagery led to attribution of sediment sources to alluvial bank erosion. Overall, our approach demonstrates how sediment source contributions and gully erosion processes shift dynamically during storm events, offering improved process understanding and more targeted management options under increasing climate extremes.

We present a unique dataset of historical tropical tree phenology observations at two sites from different bioclimatic regions across the Congo Basin. We cover both the Atlantic Mayombe forest and the tropical forest in the central Congo Basin. To our knowledge this is the complete extant historical (1937–1957) phenology data across the Congo basin. The data contains ~10 million observations of 876 species, across 6339 individuals, and phenology metrics including leaf, flowering, and fruiting phenology. The data were recovered through expert transcription and validated community science based crowdsourcing. These data may provide a reference baseline and key information on how tree species are responding to a changing climate.

In East Africa, soil is being washed away from the land into rivers faster than ever. This is because of changes in how people interact with their land, soil, and plants. First, forests were cut down to make farms. Later, growing numbers of animals overgrazed grasslands. Without trees and grasses to protect the soil, heavy rain quickly began washing it away. Steep, deep cuts in the land, called gullies, then form and keep growing faster and faster, carrying away soil, water, nutrients, and even seeds. This makes it hard for plants to grow back. In response, people are starting to take action. They are using traditional tools to slow down water, regrow plants, and fix damaged land. However, they need help from governments and scientists to apply these solutions to bigger gullies and across larger regions. Protecting healthy soils is important so that people in East African can keep producing enough food in the future.

Afrotropical ecosystems span a broad water availability gradient—from grasslands and savannas to rainforests—but even rainforests are comparatively drier than those of the Amazon or Southeast Asia. Hence water availability determines to a large extent the spatial distribution of Afrotropical ecosystems. Here we show that future greenhouse gas emissions will induce diverging trends in both total precipitation and its seasonal variability across tropical Africa’s biomes, using remotely sensed land cover types, observational datasets of historical hydroclimate and Earth system model projections. Seasonally dry forests are projected to face increasing drought stress, while non-forest vegetation will become mostly wetter. The maximum climatological water deficit of carbon-dense rainforests in the Afrotropics is expected to increase in the Northern Hemisphere and decrease in the Southern Hemisphere. Although biome transitions and net changes in carbon stocks remain limited, regional discrepancies emerge, with potential woody encroachments in grasslands offsetting rainforest declines. Our results show that, even without widespread biome collapse, emerging hydroclimatic regime shifts will reorganize where Afrotropical ecosystems can establish, with far-reaching consequences for biodiversity, the land carbon sink, and climate adaptation across tropical Africa.

Old-growth tropical forests store vast amounts of carbon in their aboveground biomass (AGB), yet the relative roles of abiotic factors such as climate, soil, and topography in governing its spatial distribution remain poorly understood. In particular, the degree to which climate acts on AGB through forest structure is still poorly quantified at the pantropical scale. Using a pantropical dataset of more than 2,000 old-growth forest plots and a structure-explicit framework, we assess how climate influences AGB through its effects on four structural attributes: basal area, mean diameter, stem density, and basal area-weighted wood density. We find that climate shapes AGB primarily through its effects on forest structure. However, structural attributes respond to climate in opposite directions, so climate’s net effect on AGB largely cancels out, and no clear climate-AGB relationship emerges across tropical regions. Moreover, only wood density responds consistently, decreasing with annual precipitation and increasing with precipitation seasonality, whereas all other attributes respond to climate differently from one region to another. This geographical variation further obscures any global climatic signal on AGB and points to the role of biogeographic history in shaping forest structure. Our findings highlight the central role of the climate-structure nexus in explaining AGB variation, and call for structure-explicit models to improve carbon stock predictions and inform climate adaptation strategies.

Abstract. Global forest assessments assist climate policy development, ecosystem science, and conservation planning, yet they rely on biomass and canopy data that do not explicitly represent the stand structural attributes derived from tree diameter measurements. This limits the ability to compare size-related structure and within-stand heterogeneity at large spatial scales. Here we present a global, spatially explicit dataset of stand-level tree diameter structure for forest cover in 2020 at 0.027° (~3 km) resolution, based on 1,203,524 georeferenced forest inventory plots comprising 54.6 million trees (≥10 cm DBH) integrated with more than 50 environmental and satellite-derived covariates into machine learning models. The dataset provides the first globally consistent maps of three complementary diameter-based metrics: arithmetic mean diameter (Dmean), quadratic mean diameter (Dqm), and the coefficient of variation of diameter (Dcv), representing average tree size, large-tree dominance, and within-stand size variability, respectively. Model performance of the ecozone-specific Random Forest framework ranged from R² = 0.41–0.82 (RMSE = 3.91–4.63 cm) for Dmean, R² = 0.43–0.83 (RMSE = 4.38–5.27 cm) for Dqm, and R² = 0.47–0.62 with (RMSE = 0.10–0.13) for Dcv across different forest ecozones. By jointly quantifying central tendency and variability in tree size, the dataset revealed spatial patterns of forest structural organization not captured by existing biomass or canopy-height products. It provides a consistent baseline for cross-biome comparison of forest structure, supporting parameterization and evaluation of vegetation and Earth system models, while offering an independent benchmark for remotely sensed structural proxies. Furthermore, it enables spatial assessment of stand structural attributes, including large-tree dominance and structural complexity, facilitating integration of diameter-based structure into global analyses of carbon dynamics and ecosystem functioning.

Within tropical forest ecosystems, wetlands such as swamp forests are an important interface between the terrestrial and aquatic landscape. Despite this assumed importance, there is a paucity of carbon flux data from wetlands in tropical Africa. Therefore, the magnitude and source of carbon dioxide (CO2) fluxes, carbon isotopic ratios, and environmental conditions were measured for 3 years between 2019 and 2022 in a seasonally flooded forest and a perennially flooded forest in the Cuvette Centrale of the Congo Basin. The mean surface fluxes for the seasonally flooded site and the perennially flooded site were 2.36 +/- 0.51 and 4.38 +/- 0.64 mu molm-2s-1, respectively. The time series data revealed no marked seasonal pattern in CO2 fluxes. As for the environmental drivers, the fluxes at the seasonally flooded site exhibited a positive correlation with soil temperature and soil moisture. Additionally, the water level appeared to be a significant factor, demonstrating a quadratic relationship with the soil fluxes at the seasonally flooded site. delta 13C values showed a progressive increase across the carbon pools, from aboveground biomass to leaf litter and then to soil organic carbon (SOC). However, there was no significant difference in delta 13C enrichment between SOC and soil-respired CO2. This lack of enrichment can be attributed to either a significant contribution from the autotrophic component of soil respiration or closed system dynamics.An in-situ-derived gas transfer velocity (k600=2.95 cm h-1) was used to calculate the aquatic CO2 fluxes at the perennially flooded site. Despite the low k600, relatively high CO2 surface fluxes were found due to very high partial pressure of CO2 (pCO2) values measured in the flooding waters. Overall, these results offer a quantification of the CO2 fluxes from forested wetlands and provide insights into the temporal variability of these fluxes and their sensitivity to environmental drivers.