Dataset Information

Contrasting biogeochemical characteristics of the Oubangui River and tributaries (Congo River basin).

ABSTRACT: The Oubangui is a major tributary of the Congo River. We describe the biogeochemistry of contrasting tributaries within its central catchment, with watershed vegetation ranging from wooded savannahs to humid rainforest. Compared to a 2-year monitoring record on the mainstem Oubangui, these tributaries show a wide range of biogeochemical signatures, from highly diluted blackwaters (low turbidity, pH, conductivity, and total alkalinity) in rainforests to those more typical for savannah systems. Spectral analyses of chromophoric dissolved organic matter showed wide temporal variations in the Oubangui compared to spatio-temporal variations in the tributaries, and confirm that different pools of dissolved organic carbon are mobilized during different hydrological stages. ?(13)C of dissolved inorganic carbon ranged between -28.1‰ and -5.8‰, and was strongly correlated to both partial pressure of CO2 and to the estimated contribution of carbonate weathering to total alkalinity, suggesting an important control of the weathering regime on CO2 fluxes. All tributaries were oversaturated in dissolved greenhouse gases (CH4, N2O, CO2), with highest levels in rivers draining rainforest. The high diversity observed underscores the importance of sampling that covers the variability in subcatchment characteristics, to improve our understanding of biogeochemical cycling in the Congo Basin.

SUBMITTER: Bouillon S

PROVIDER: S-EPMC4066439 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Contrasting biogeochemical characteristics of the Oubangui River and tributaries (Congo River basin).

Bouillon Steven S Yambélé Athanase A Gillikin David P DP Teodoru Cristian C Darchambeau François F Lambert Thibault T Borges Alberto V AV

Scientific reports 20140623

The Oubangui is a major tributary of the Congo River. We describe the biogeochemistry of contrasting tributaries within its central catchment, with watershed vegetation ranging from wooded savannahs to humid rainforest. Compared to a 2-year monitoring record on the mainstem Oubangui, these tributaries show a wide range of biogeochemical signatures, from highly diluted blackwaters (low turbidity, pH, conductivity, and total alkalinity) in rainforests to those more typical for savannah systems. Sp ...[more]

PMID: 24954525

Similar Datasets

Project description:Optical-biogeochemical relationships of particulate and dissolved organic matter are presented in support of remote sensing of the Baltic Sea pelagic. This system exhibits strong seasonality in phytoplankton community composition and wide gradients of chromophoric dissolved organic matter (CDOM), properties which are poorly handled by existing remote sensing algorithms. Absorption and scattering properties of particulate matter reflected the seasonality in biological (phytoplankton succession) and physical (thermal stratification) processes. Inherent optical properties showed much wider variability when normalized to the chlorophyll-a concentration compared to normalization to either total suspended matter dry weight or particulate organic carbon. The particle population had the largest optical variability in summer and was dominated by organic matter in both seasons. The geographic variability of CDOM and relationships with dissolved organic carbon (DOC) are also presented. CDOM dominated light absorption at blue wavelengths, contributing 81% (median) of the absorption by all water constituents at 400 nm and 63% at 442 nm. Consequentially, 90% of water-leaving radiance at 412 nm originated from a layer (z90) no deeper than approximately 1.0 m. With water increasingly attenuating light at longer wavelengths, a green peak in light penetration and reflectance is always present in these waters, with z90 up to 3.0-3.5 m depth, whereas z90 only exceeds 5 m at biomass < 5 mg Chla m-3. High absorption combined with a weakly scattering particle population (despite median phytoplankton biomass of 14.1 and 4.3 mg Chla m-3 in spring and summer samples, respectively), characterize this sea as a dark water body for which dedicated or exceptionally robust remote sensing techniques are required. Seasonal and regional optical-biogeochemical models, data distributions, and an extensive set of simulated remote-sensing reflectance spectra for testing of remote sensing algorithms are provided as supplementary data.

Project description:The Yellow River Basin (YRB) is China's substantial energy consumption base. The issue of carbon emission efficiency directly affects the ecological protection and high-quality development of the YRB. It is the key to achieving carbon peak in 2030 and carbon neutralization in 2060 ("30.60") double carbon emission reduction targets. Therefore, taking YRB as the research object, this paper first calculates the carbon emission and the decoupling state in the YRB. Secondly, the super-efficiency slacks-based measurement (SE-SBM) model is combined with the Malmquist index to analyze the temporal and spatial evolution characteristics of YRB's carbon emission efficiency from static and dynamic perspectives. Thirdly, the dynamic evolution characteristics of carbon emission efficiency are analyzed with the help of the Kernel density function. Finally, the Tobit model analyzes the influencing factors of YRB's and China's carbon emission efficiency. The results show that: (1) Among the nine provinces of YRB, the decoupling state between carbon emissions and economic growth in most provinces changes from weak decoupling to strong decoupling, and the decoupling elasticity index shows a fluctuating downward trend. (2) There are significant differences in carbon emission efficiency among provinces, but on the whole, it shows a stable growth trend. The high-value area of carbon emission efficiency is increasing, and the phenomenon of two-level differentiation is improving. The decline of the technological progress index causes the Malmquist index in Qinghai and Ningxia. On the contrary, the rise of the Malmquist index in the other seven provinces is caused by improving the technical efficiency index. (3) Industrial structure, economic development, and industrialization are the main positive factors affecting YRB's carbon emission efficiency. Urbanization level, green development level, and energy consumption level are the leading negative indicators hindering YRB's improvement of carbon emission efficiency. Therefore, targeted emission reduction suggestions should be formulated according to YRB's resource endowment and development stage characteristics.

Dataset Information

Contrasting biogeochemical characteristics of the Oubangui River and tributaries (Congo River basin).

Publications

Contrasting biogeochemical characteristics of the Oubangui River and tributaries (Congo River basin).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets