Search Results (44)

Accurately understanding the changes in global light-response parameters (i.e., maximum light use efficiency, LUEmax) is essential for improving the simulation of terrestrial ecosystem’s photosynthetic carbon cycling under climate change, but a comprehensive understanding and assessments are still lacking. In this study, LUEmax was quantified using data from 23 global flux stations, and the change patterns in LUEmax across various vegetation types and climate zones were analyzed. The extent of significant increases or decreases in LUEmax during different phenological stages of vegetation growth was evaluated using trend analysis methods. The contribution rates of environmental factors were determined using the Geodetector method. The results show that the LUEmax values of the same vegetation type varied across different climate types. More variable climates (e.g., polar and alpine climates) are associated with more significant fluctuations in LUEmax. Conversely, more stable climates (e.g., temperate climates) tend to show more consistent LUEmax values. Within the same climate type, evergreen needleleaf forests (ENF) and deciduous broadleaf forests (DBF) generally exhibited higher LUEmax values in temperate and continental climates, whereas the LUEmax values of wetlands (WET) were relatively high in polar and alpine climates. The mechanisms driving variations in LUEmax across different vegetation types exhibited significant disparities under diverse environmental conditions. For ENF and DBF, LUEmax is predominantly influenced by temperature and radiation. In contrast, the LUEmax of GRA, WET, and croplands is more closely associated with vegetation indices and temperature factors. The findings of this study play an important role in advancing the theoretical development of gross primary productivity (GPP) models and enhancing the accuracy of carbon sequestration simulations in terrestrial ecosystems. Full article

The latest versions of the Ross-Li model include kernels that represent isotropic reflection of the surface, describe backward reflection of soil and vegetation systems, characterize strong forward reflection of snow, and adequately consider the hotspot effect (i.e., RossThick-LiSparseReciprocalChen-Snow, RTLSRCS), theoretically able to effectively characterize BRDF/Albedo/NBAR features for various land surface types. However, a systematic evaluation of the RTLSRCS model is still lacking for various land cover types. In this paper, we conducted a thorough assessment of the RTLSRCS and RossThick-LiSparseReciprocalChen (RTLSRC) models in characterizing BRDF/Albedo/NBAR characteristics by using the global POLDER BRDF database. The primary highlights of this paper include the following: (1) Both models demonstrate high accuracy in characterizing the BRDF characteristics across 16 IGBP types. However, the accuracy of the RTLSRC model is notably reduced for land cover types with high reflectance and strong forward reflection characteristics, such as Snow and Ice (SI), Deciduous Needleleaf Forests (DNF), and Barren or Sparsely Vegetated (BSV). In contrast, the RTLSRCS model shows a significant improvement in accuracy for these land cover types. (2) These two models exhibit highly consistent albedo inversion across various land cover types (R² > 0.9), particularly in black-sky and blue-sky albedo, except for SI. However, significant differences in white-sky albedo inversion persist between these two models for Evergreen Needleleaf Forests (ENF), Evergreen Broadleaf Forests (EBF), Urban Areas (UA), and SI (p < 0.05). (3) The NBAR values inverted by these two models are nearly identical across the other 15 land cover types. However, the consistency of NBAR results is relatively poor for SI. The RTLSRC model tends to overestimate compared to the RTLSRCS model, with a noticeable bias of approximately 0.024. This study holds significant importance for understanding different versions of Ross-Li models and improving the accuracy of satellite BRDF/Albedo/NBAR products. Full article

The vegetation patterns in high-latitude and high-altitude regions (HLAR) of the Northern Hemisphere are undergoing significant changes due to the combined effects of global warming and human activities, leading to increased uncertainties in vegetation phenological assessment. However, previous studies on vegetation phenological changes often relied on long-term time series of remote sensing products for evaluation and lacked comprehensive analysis of driving factors. In this study, we utilized high temporal resolution seamless MODIS products (MODIS-NDVI_SDC and MODIS-EVI2_SDC) to assess the vegetation phenological changes in High-Latitude-Altitude Regions (HLAR) of the Northern Hemisphere. We quantified the differences in vegetation phenology among different land-use types and determined the main driving factors behind vegetation phenological changes. The results showed that the length of the growing season (LOS) derived from MODIS-NDVI_SDC was 8.9 days longer than that derived from MODIS-EVI2_SDC, with an earlier start of the growing season (SOS) by 1.5 days and a later end of the growing season (EOS) by 7.4 days. Among different vegetation types, deciduous needleleaf forests exhibited the fastest LOS extension (p < 0.01), while croplands showed the fastest LOS reduction (p < 0.05). Regarding land-use transitions, the conversion of built-up land to forest and grassland had the longest LOS. In expanding agricultural areas, the LOS of land converted from built-up land to cropland was significantly higher than that of other land conversions. We analyzed human activities and found that as the human footprint gradient increased, the LOS showed a decreasing trend. Among the climate-related factors, the dominant response of phenology to temperature was the strongest in the vegetation greening period. During the vegetation browning period, the temperature control was weakened, and the control of radiation and precipitation was enhanced, accounting for 20–30% of the area, respectively. Finally, we supplement and prove that the highest contributions to vegetation greening in the Northern Hemisphere occurred during the SOS period (May–June) and the EOS period (October). Our study provides a theoretical basis for vegetation phenological assessment under global change. It also offers new insights for land resource management and planning in high-latitude and high-altitude regions. Full article

Carbon utilization efficiency (CUE) in terrestrial ecosystems stands as a pivotal metric for assessing ecosystem functionality. Investigating the spatiotemporal dynamics of regional CUE within the context of global climate change not only provides a theoretical foundation for understanding terrestrial carbon cycling but also furnishes essential data support for formulating sustainable management strategies at a regional scale. This study focuses on the southeastern region of Tibet. Utilizing monthly and yearly MOD17A2HGF as primary sources, we employ Thiel–Sen estimation and Mann–Kendall trend analysis to scrutinize the spatiotemporal dynamics of CUE. Systematic analysis of the stability of CUE spatiotemporal changes in the Southeast Tibet region is conducted using the coefficient of variation analysis. The Hurst model is then applied to prognosticate future CUE changes in Southeast Tibet. Additionally, a comprehensive analysis of CUE is undertaken by integrating meteorological data and land-use data. The findings reveal the following: (1) At the monthly scale, regional CUE exhibits discernible variations synchronized with the growth season, with different vegetation types displaying diverse fluctuation patterns. The high-altitude forest area manifests the least annual CUE fluctuations, while evergreen needleleaf forests and evergreen broadleaf forests demonstrate larger variations. At the yearly scale, CUE reveals a non-significant upward trend overall, but there is an augmented fluctuation observed from 2019 to 2022. (2) CUE in Southeast Tibet demonstrates sensitivity to temperature and precipitation variations, with temperature exhibiting a more pronounced and strongly correlated impact, especially in Gongjo County and Qamdo Town. Temperature and precipitation exert opposing influences on CUE changes in the Southeast Tibet region. In the southern (below 28° N) and northern (above 31° N) regions of Southeast Tibet, the response of CUE to temperature and precipitation variations differs. Moreover, over 62.3% of the areas show no sustained trend of change. (3) Vegetation type emerges as a principal factor determining the scope and features of vegetation CUE changes. Grassland and sparse grassland areas exhibit markedly higher CUE values than evergreen broadleaf forests, deciduous broadleaf forests, evergreen needleleaf forests, and deciduous needleleaf forests. Notably, the CUE fluctuation in shrublands and areas with embedded farmland vegetation surpasses that of other vegetation types. Full article

Recent research has mapped potential afforestation land to support China’s goal of achieving “carbon neutrality” and has proposed tree species selection to maximize carbon uptake. However, it overlooked biophysical climatic effects, which have a more significant impact on local temperature than CO₂ reduction. This study aims to present a comprehensive understanding of how afforestation in China affects local and regional climates through biophysical processes. It focuses on the latitudinal patterns of land surface temperature differences (ΔLST) between five locally adapted forest types and adjacent grasslands using satellite-based observations. Our key findings are as follows: Firstly, broadleaf forests and mixed forests exhibit a stronger cooling effect than coniferous forests due to differences in canopy structure and distribution. Specifically, the net cooling effects of evergreen broadleaf forests (EBFs), deciduous broadleaf forests (DBFs), and mixed forests (MFs) compared to grasslands are −0.50 ± 0.10 °C (mean ± 95% confidence interval), −0.33 ± 0.05 °C, and −0.36 ± 0.06 °C, respectively, while evergreen needleleaf forests (ENFs) compared to grasslands are −0.22 ± 0.11 °C. Deciduous needleleaf forests (DNFs) exhibit warming effects, with a value of 0.69 ± 0.24 °C. In regions suitable for diverse forest types planting, the selection of broadleaf and mixed forests is advisable due to their enhanced local cooling impact. Secondly, temperate forests have a net cooling effect to the south of 43° N, but they have a net warming effect to the north of 48° N compared to grasslands. We recommend caution when planting DNFs, DBFs, and MFs in northeastern China, due to the potential for local warming. Thirdly, in the mountainous areas of southwestern China, especially when planting ENFs and MFs, tree planting may lead to local warming. Overall, our study provides valuable supplementary insights to China’s existing afforestation roadmap, offering policy support for the country’s climate adaptation and mitigation efforts. Full article

The increase in global carbon emissions has intensified the effects of CO₂ fertilization on the carbon cycle. CO₂ fertilization is shaped by several factors, including the physiological differences among trees of varied forest ages and types, as well as the influence of different climatic conditions. It is essential to investigate the differences in CO₂ fertilization effects across diverse climate zones and delve into the association between these effects and forest age and type. Such exploration will deepen our knowledge of forest responses to environmental changes. This study used annual ring width data from the International Tree-Ring Data Bank, employing the generalized additive mixed models and the Random Forest model to discern the pattern of the CO₂ fertilization effect concerning forest age in the Northern Hemisphere. This study also explored the variations in the effect of CO₂ fertilization across unique climate zones and the disparities among various forest types within the same climatic zone. The results indicated a link between forest age and the CO₂ fertilization effect: it tends to increase in sapling forests and middle-aged forests and diminish in mature forests. Warmer, drier environments had a more marked effect of increased CO₂ on tree fertilization. Additionally, coniferous forests demonstrated a more substantial CO₂ fertilization effect than broadleaf forests, and deciduous needle-leaf forests surpassed evergreen needle-leaf forests in this regard. This research is pivotal in understanding the shifting patterns of CO₂ fertilization effects and how forests respond to atmospheric changes. Full article

Carbon emissions from forest fires release large amounts of carbon and have important implications for the global and regional carbon cycle and atmospheric carbon concentrations. Considering the significant spatial and temporal variations in different forest fires, this study explores the relationship between different forests and carbon emissions from forest fires. This study developed a high-resolution (0.05° × 0.05°) daily global inventory of carbon emissions from biomass burning during 2016–2022. The inventory estimates of carbon emissions from biomass burning are based on the newly released FY-3 data product, satellite and observational data of biomass density, and spatial and temporal variable combustion factors. Forest fire carbon emissions were assessed using active fire data from FY-3 series satellites from 2016 to 2022, and it was linearly compared with GFED, FEER, and GFAS data on time and spatial scales with R² of 0.7, 0.73, and 0.69, respectively. The results show spatial patterns of forest cover and carbon emissions, with South America, Africa, South-East Asia, and northern Asia as high-emission zones. The analysis shows an overall upward trend in global forest fire carbon emissions over the study period. Different types of forests exhibited specific emission patterns and temporal variations. For example, most needleleaf forest fires occur in areas with low tree cover, while broadleaf forest fires tend to occur in areas with high tree cover. The study showed that there was a relationship between inter-annual trends in forest fire carbon emissions and land cover, with biomass burning occurring mainly in the range of 60–70% tree cover. However, there were also differences between evergreen broadleaf forest, evergreen needleleaf forest, deciduous broadleaf forest, deciduous needleleaf forest, and mixed forest indicating the importance of considering differences in forest types when estimating emissions. This study identifies the main sources of carbon emissions from forest fires globally, which will help policymakers to take more targeted measures to reduce carbon emissions and provide a reliable basis for appropriate measures and directions in future carbon mitigation actions. Full article

Land surface microwave emissivity is crucial to the accurate retrieval of surface and atmospheric parameters and the assimilation of microwave data into numerical models over land. The microwave radiation imager (MWRI) sensors aboard on Chinese FengYun-3 (FY-3) series satellites provide valuable measurements for the derivation of global microwave physical parameters. In this study, an approximated microwave radiation transfer equation was used to estimate land surface emissivity from MWRI by using brightness temperature observations along with corresponding land and atmospheric properties obtained from ERA-Interim reanalysis data. Surface microwave emissivity at the 10.65, 18.7, 23.8, 36.5, and 89 GHz vertical and horizontal polarizations was derived. Then, the global spatial distribution and spectrum characteristics of emissivity over different land cover types were investigated. The seasonal variations of emissivity for different surface properties were presented. Furthermore, the error source was also discussed in our emissivity derivation. The results showed that the estimated emissivity was able to capture the major large-scale features and contains a wealth of information regarding soil moisture and vegetation density. The emissivity increased with the increase in frequency. The smaller surface roughness and increased scattering effect may result in low emissivity. Desert regions showed high emissivity microwave polarization difference index (MPDI) values, which suggested the high contrast between vertical and horizontal microwave signals in this region. The emissivity of the deciduous needleleaf forest in summer was almost the greatest among different land cover types. There was a sharp decrease in the emissivity at 89 GHz in the winter, possibly due to the influence of deciduous leaves and snowfall. The land surface temperature, the radio-frequency interference, and the high-frequency channel under cloudy conditions may be the main error sources in this retrieval. This work showed the potential capabilities of providing continuous and comprehensive global surface microwave emissivity from FY-3 series satellites for a better understanding of its spatiotemporal variability and underlying processes. Full article

The net primary productivity (NPP) of vegetation is an important indicator reflecting the vegetation dynamics and carbon sequestration capacity in a region. In recent years, China has implemented policies to carry out ecological protection. To understand the changes in the distribution of vegetation NPP in China and the influence of climate factors, the Carnegie–Ames–Stanford approach (CASA) model was used to estimate the NPP from 2001 to 2020. In this paper, several sets of measurement datasets and products were collected to evaluate the effectiveness of the model and suggestions were provided for the modification of the CASA model based on the evaluation results. In addition to the correlation analysis, this paper presents a statistical method for analyzing the quantitative effects in individual climatic factors on NPP changes in large regions. The comparison found that the model has a better estimation effect on grassland and needleleaf forest. The estimation error for the evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF) decreases with the warming of the climatic zone, while the evergreen broadleaf forest (EBF) and deciduous needleleaf forest (DNF) do the opposite. The changes in total CASA NPP were consistent with the trends of other products, showing a dynamic increasing trend. In terms of the degree of correlation between the NPP changes and climatic factors, the NPP changes were significantly correlated with temperature in about 10.39% of the vegetation cover area and with precipitation in about 26.92% of the vegetation cover area. It was found that the NPP variation had a negative response to the temperature variation in Inner Mongolia grasslands, while it had a positive but small effect (±10 g C) in the Qinghai–Tibet Plateau grasslands. Precipitation had a facilitative effect on the grassland NPP variation, while an increase in the annual precipitation of more than 200 mm had an inhibitory effect in arid and semi-arid regions. This study can provide data and methodological reference for the ecological assessment of large-scale regional and climate anomalous environments. Full article

With climate change, frequent forest fires and prolonged fire period occur all over the world. Moreover, carbon emission from forest fire affects the carbon cycle of the forest ecosystem. However, this effect varies by region with no uniform conclusions, and fewer comparative studies exist on such differences between regions. In this paper, net primary productivity (NPP) data MOD17A3 were used as an important parameter of forest carbon absorption, along with MODIS fire spot data MCD14DL and burned area data MCD64A1. Forest carbon lost under forest fire interference in the northeast and southwest natural forest areas of China was studied to explore the role of forest fire in the carbon cycle process and its differences in the unlike regions of China. Here, by means of kernel density analysis and M-K trend test, the characteristics of forest fires in China’s southwest and northeast forests were calculated. Forest carbon emission under forest fire disturbance was quantified by reference to the forest fire emission factor list. We show that (1) the total number of forest fire spots in the southwest region from 2001 to 2020 was 1.06 × 10⁵, 1.28 times that of Northeast China. However, the total burned area in the southwest was only 67.84% of that in the northeast. (2) The total carbon emissions from forest fires in the southwest from 2001 to 2020 was 37,559.94 Gg, 10.77% larger than the northeast forest, CH₄ and CO₂ were 13.52% and 11.29% larger respectively. Moreover, the carbon emissions of forest fire in the northeast showed a downward trend, R² = 0.16 (p < 0.1), while it remained basically unchanged in the southwest. The contribution of carbon emissions from forest fires changed with forest types, it was shown as: evergreen needleleaf forest (14.98%) > evergreen broadleaf forest (10.81%) > deciduous needleleaf forest (6.52%) > deciduous broadleaf forest (5.22%). (3) From 2001 to 2020, under the premise that the NPP both manifested upward trends, the NPP of the burned areas showed a significant downward trend in the southwest forest, with R² = 0.42 (p < 0.05), while it increased in the northeast forest, with R² = 0.37 (p < 0.05). It showed negative correlation between NPP of burned areas and forest fire carbon emissions, and forest fire disturbance had no significant effect on forest NPP in Northeast China, while net carbon loss occurred in Southwest China. In general, under different forest fire characteristics, NPP, which represents forest carbon uptake, and carbon emissions from forest fires show differences. The impact of forest fire disturbance on forest carbon process varies with regions. The study can provide some ideas on the effects of forest fire disturbance on climate change. Full article

The Gulf of Corinth is a semi-isolated basin in central Greece interrupting the Pindus Mountain Range, which nowadays is a biodiversity hotspot. Considering its key location, deep drilling was carried out within the International Ocean Discovery Program (IODP; Expedition 381: Corinth Active Rift Development) aiming to improve our understanding of climatic and environmental evolution in the region. Here, we present a new long pollen record from a Mediterranean setting in the southernmost tip of the Balkan Peninsula recording the vegetation succession within the Quaternary. The Corinth pollen record shows no major shifts in arboreal pollen between glacial and interglacial intervals, while Mediterranean and mesophilous taxa remain abundant throughout the study interval. During interglacials, the most frequent reconstructed biomes are cool mixed evergreen needleleaf (CMIX) and deciduous broadleaf forests (DBWB), while graminoid with forb (GRAM) and xerophytic shrubs (XSHB) dominate within glacials. Our findings support the hypothesis that the study area was a significant refugium, providing suitable habitats for Mediterranean, mesophilous and montane trees during successive Quaternary climate cycles. Full article

The GEDI LiDAR system was specifically designed to detect vegetation structure and has proven to be a suitable tool for estimating forest biophysical parameters, especially canopy height, at a global scale. This study compares the GEDI relative height metric (RH100) over different forest types, especially deciduous broadleaf and evergreen coniferous located in Thuringia, Germany, to understand how the forest structural differences affect the GEDI height estimation. A canopy height model that was produced using digital terrain and surface models (DTM and DSM) derived from airborne laser scanning data is used as the reference data. Based on the result, GEDI canopy height over needleleaf forest is slightly more accurate (RMSE = 6.61 m) than that over broadleaf (RMSE = 8.30 m) and mixed (RMSE = 7.94 m) forest. Evaluation of the GEDI acquisition parameters shows that differences in beam type, sensitivity, and acquisition time do not significantly affect the accuracy of canopy heights, especially over needleleaf forests. Considering foliage condition impacts on canopy height estimation, the contrasting result is observed in the broadleaf and needleleaf forests. The GEDI dataset acquired during the winter when deciduous species shed their leaves (the so-called leaf-off dataset), outperforms the leaf-on dataset in the broadleaf forest but shows less accurate results for the needleleaf forest. Considering the effect of the plant area index (PAI) on the accuracy of the GEDI canopy height, the GEDI dataset is divided into two sets with low and high PAI values with a threshold of median PAI = 2. The results show that the low PAI dataset (median PAI < 2) corresponds to the non-growing season (autumn and winter) in the broadleaf forest. The slightly better performance of GEDI using the non-growing dataset (RMSE = 7.40 m) compared to the growing dataset (RMSE = 8.44 m) in the deciduous broadleaf forest and vice versa, the slightly better result using the growing dataset (RMSE = 6.38 m) compared to the non-growing dataset (RMSE = 7.24 m) in the evergreen needleleaf forest is in line with the results using the leaf-off/leaf-on season dataset. Although a slight improvement in canopy height estimation was observed using either the leaf-off or non-growing season dataset for broadleaf forest, and either the leaf-on or growing season dataset for needleleaf forest, the approach of filtering GEDI data based on such seasonal acquisition time is recommended when retrieving canopy height over pure stands of broadleaf or needleleaf species, and the sufficient dataset is available. Full article

The vast forests of Northeast China are under great pressure from climate change. Understanding the effects of changing climate conditions on spring phenology is of great significance to assessing the stability of regional terrestrial ecosystems. Using Normalized Difference Vegetation Index data from 1982 to 2013, this paper investigated the changes in the start date of the vegetation growing season (SOS) of two main forest types in Northeast China, analyzing the changes in temporal and spatial patterns of forest spring phenology before and during the recent short-term warming slowdown, and exploring the effects of day and night temperatures and precipitation on the start of the growing season. The results showed that, during the rapid warming period (1982–1998), the SOS of deciduous needleleaf forests (DNF) was significantly advanced (−0.428 days/a, p < 0.05), while the rate of advance of SOS of deciduous broadleaf forests (DBF) was nonsignificant (−0.313 days/a, p > 0.10). However, during the short-term slowdown (1998–2013), the SOS of DBF was strongly delayed (0.491 days/a, p < 0.10), while the change in SOS of DNF was not significant (0.169 days/a, p > 0.10). The SOS was sensitive to spring maximum temperature for both forest types during the analysis period. Increases in winter precipitation influenced the SOS during the rapid warming period for DNF; this combined with the increase in the spring maximum temperature contributed to the advance in SOS. The decrease in the spring maximum temperature during the short-term slowdown, combined with a decrease in the previous summer maximum temperature, contributed to the rapid delay of SOS for DBF. DBF SOS was also more influenced by lagged effects of prior conditions, such as previous autumn to spring precipitation during the rapid warming period and previous summer maximum temperature during the short-term slowdown. In general, SOS was mainly determined by changes in daytime thermal conditions; DNF is more sensitive to temperature increases and DBF is more sensitive to decreases. Different regional climate conditions lead to differences in the distribution of DNF and DBF, as well as in the response of SOS to climate change during the rapid warming and short-term slowdown periods. Full article

Subsoil (0.2–1 m) organic carbon (C) accounts for the majority of soil organic carbon (SOC), and SOC turnover time (τ, year) is an important index of soil C stability and sequestration capacity. However, the estimation of subsoil τ and the identification of its dominant environmental factors at a regional scale is lacking in regards to forest ecosystems. Therefore, we compiled a dataset with 630 observations to investigate subsoil τ and its influencing factors in forest ecosystems across China using the structural equation model (SEM). The results showed a large variability of subsoil τ from 2.3 to 896.2 years, with a mean (± standard deviation) subsoil τ of 72.4 ± 68.6 years; however, the results of one-way analysis of variance (ANOVA) showed that subsoil τ differed significantly with forest types (p = 0.01), with the slowest subsoil τ obtained in deciduous-broadleaf forests (82.9 ± 68.7 years), followed by evergreen-needleleaf forests (77.6 ± 60.8 years), deciduous-needleleaf forests (75.3 ± 78.6 years), and needleleaf and broadleaf mixed forests (71.3 ± 80.9 years), while the fastest subsoil τ appeared in evergreen-broadleaf forests (59.9 ± 40.7 years). Subsoil τ negatively correlated with the mean annul temperature, occurring about three years faster with a one degree increase in temperature, indicating a faster subsoil SOC turnover under a warming climate. Subsoil τ significantly and positively correlated with microbial activities (indicated by microbial C and nitrogen), highlighting the importance of microbial communities in regulating subsoil C dynamics. Climate, forest types, forest origins, vegetation, and soil variables explained 37% of the variations in subsoil τ, as indicated by the SEM, and the soil property was the most important factor affecting subsoil τ. This finding challenged previous perception that climate was the most important factor driving subsoil C dynamics, and that dominant drivers varied according to climate zones. Therefore, recognizing different dominant factors in predicting subsoil C dynamics across climate zones would improve our understanding and reduce the uncertainties regarding subsoil C dynamics in biogeochemical models under ongoing climate change. Full article

We studied two medium size pristine rivers (Taz and Ket) of boreal and subarctic zone, western Siberia, for a better understanding of the environmental factors controlling major and trace element transport in riverine systems. Our main objective was to test the impact of climate and land cover parameters (permafrost, vegetation, water coverage, soil organic carbon, and lithology) on carbon, major and trace element concentration in the main stem and tributaries of each river separately and when considering them together, across contrasting climate/permafrost zones. In the permafrost-bearing Taz River (main stem and 17 tributaries), sizable control of vegetation on element concentration was revealed. In particular, light coniferous and broadleaf mixed forest controlled DOC, and some nutrients (NO₂, NO₃, Mn, Fe, Mo, Cd, Ba), deciduous needle-leaf forest positively correlated with macronutrients (PO₄, P_tot, Si, Mg, P, Ca) and Sr, and dark needle-leaf forest impacted N_tot, Al, and Rb. Organic C stock in the upper 30–100 cm soil positively correlated with Be, Mn, Co, Mo, Cd, Sb, and Bi. In the Ket River basin (large right tributary of the Ob River) and its 26 tributaries, we revealed a correlation between the phytomass stock at the watershed and alkaline-earth metals and U concentration in the river water. This control was weakly pronounced during high-water period (spring flood) and mostly occurred during summer low water period. Pairwise correlations between elements in both river systems demonstrated two group of solutes—(1) positively correlated with DIC (Si, alkalis (Li, Na), alkaline-earth metals (Mg, Ca, Sr, Ba), and U), this link originated from groundwater feeding of the river when the labile elements were leached from soluble minerals such as carbonates; and (2) elements positively correlated with DOC (trivalent, tetravalent, and other hydrolysates, Se and Cs). This group reflected mobilization from upper silicate mineral soil profile and plant litter, which was strongly facilitated by element colloidal status, notably for low-mobile geochemical tracers. The observed DOC vs DIC control on riverine transport of low-soluble and highly mobile elements, respectively, is also consistent with former observations in both river and lake waters of the WSL as well as in soil waters and permafrost ice. A principal component analysis demonstrated three main factors potentially controlling the major and TE concentrations. The first factor, responsible for 26% of overall variation, included aluminum and other low mobile trivalent and tetravalent hydrolysates, Be, Cr, Nb, and elements strongly complexed with DOM such as Cu and Se. This factor presumably reflected the presence of organo-mineral colloids, and it was positively affected by the proportion of forest and organic C in soils of the watershed. The second factor (14% variation) likely represented a combined effect of productive litter in larch forest growing on carbonate-rich rocks and groundwater feeding of the rivers and acted on labile Na, Mg, Si, Ca, P, and Fe(II), but also DOC, micronutrients (Zn, Rb, Ba), and phytomass at the watershed. Via applying a substituting space for time approach for south-north gradient of studied river basins, we predict that climate warming in northern rivers may double or triple the concentration of DIC, Ca, Sr, U, but also increase the concentration of DOC, POC, and nutrients. Full article