Search

("Dissolved organic carbon leaching flux in a mixed agriculture and forest watershed in Rwanda" [1]). This article presents data of leached dissolved organic carbon (LDOC), stream water dissolved organic carbon), rainfall amount (Ra), rainfall intensity (Ri), rainfall soil storage (S), runoff (Q), and soil properties such as total organic carbon (TOC), total nitrogen (TN), cation exchange capacity (CEC), and soil texture data collected in the Rukarara River Watershed (RRW), a tropical watershed. All these data were used to analyze leached dissolved organic carbon (LDOC) fluxes in the watershed and their relationship with stream DOC. LDOC and soil properties data were collected at three sites in multiple plots per site located in natural forest (NF), tea plantations (TP), plantation forests (PF), and croplands (CL). Twenty-three plots in total were sampled to collect LDOC data. Soil properties data were analyzed from soil samples collected nearby the plots. Soil texture elements data were used to calculate soil porosity and saturated hydraulic conductivity (Ks). Data of stream DOC were analyzed from water samples collected and analyzed in the laboratory using a TOC analyzer. Rainfall data were recorded within the RRW using tipping bucket rain gauges installed at three sites. These rainfall data were used to calculate rainfall intensity, potential surface runoff, and rainfall soil storage., Competing Interests: None., (© 2020 The Authors.)

("Sources of soil dissolved organic carbon in a mixed agricultural and forested watershed in Rwanda", [6]) This data article presents water extractable organic carbon (WEOC), percolation water dissolved organic carbon (pDOC), and mean antecedent precipitation indices (API) and mean antecedent temperature (MAT) data. The article also presents edaphic properties such soil texture elements, total organic carbon (TOC), total nitrogen (TN), cation exchange capacity (CEC), iron (Fe), and aluminum (Al). Additionally, the article presents topography attributes such including topographic position index (TPI) and curvature. All these data were used to analyze both WEOC and pDOC dynamics in the Rukarara River Watershed (RRW), Rwanda. WEOC and soil properties data were analyzed from sampled 52 soil composites samples collected during from October to December 2016 using 53 × 50 mm rings. Data of pDOC were analyzed from percolation water samples collected using a zero tension lysimeters on various dates during the period from Jun 2015 to Jun 2017. API and MAT data for various antecedent days were calculated on basis of rainfall and air temperature data recorded at three stations within the RRW using respectively tipping bucket rain gauges and sensors installed at three sites located representing the main land use land cover classes within the RRW., (© 2019 The Author(s).)

Dissolved organic carbon (DOC) loading is rarely estimated in tropical watersheds. This study quantifies DOC loading in the Rukarara River Watershed (RRW), a Rwandan tropical forest and agricultural watershed, and evaluates its relationship with hydrological factors, land use and land cover (LULC), and topography to better understand the impact of stream DOC export on watershed carbon budgets. The annual average load for the study period was 977.80 kg C, which represents approximately 8.44% of the net primary productivity of the watershed. The mean daily exports were 0.37, 0.14, 0.075 and 0.32 kg C/m 2 in streams located in natural forest, tea plantation, small farming areas, and at the outlet of the river, respectively. LULC is a factor that influences DOC loading. The quick flow was the main source of stream DOC at all study sites. Stream DOC increases with increasing water flow, indicating a positive relationship. Thus, the expectation is that a change in land cover and/or rainfall will result in a change of stream DOC dynamics within the watershed. Topography was also found to influence the dynamics of stream DOC through its effect on overland flow in terms of drainage area and total length of flow paths. Tea plantations were located in areas of high drainage density and projected increase of rainfall in the region, as a consequence of climate change, could increase stream DOC content and affect stream water quality, biodiversity, balance between autotrophy and heterotrophy, and bioavailability of toxic compounds within the RRW., (Copyright © 2018 Elsevier B.V. All rights reserved.)

This data article presents water stage, flow, and net primary productivity (NPP) data that were used to analyze the dynamics of the riverine dissolved organic carbon (DOC) dynamics in the Rukarara River watershed in Rwanda. We measured water stage data every 15 min and calculated daily averages used to estimate flow based on rating curves. The rating curves were produced using several measured contemporaneous water stage and flow data. Estimated flow data were used to calculate water dissolved organic carbon (DOC) loadings separate the total stream flow into quick and baseflow. Annual NPP data for a 15-year period were used to estimate the effect of proportion of stream DOC loading on carbon sequestration within the Rukarara River watershed.

Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts.