• Energy Research
• 2016-2025close

AbstractThe FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

AbstractPastoral systems are the dominant livestock production system in arid and semiarid regions of sub‐Saharan Africa (SSA). They are often the only form of agriculture that can be practiced due to unfavorable climate and soil fertility levels that prevent crop cultivation. Pastoralism can have negative impacts on the environment, including land degradation, greenhouse gas emissions and other gases to the atmosphere, soil erosion, water pollution and biodiversity loss. Here, we review the current knowledge on nitrogen (N) cycling, storage, and loss pathways, with an emphasis on identification of N emission hotspots. Our review reports a large uncertainty in the amount of N lost as ammonia from excreta and manure storage, as well as N losses via nitrate and DON leaching. We also found that another major N loss pathway (18%), soil N2 emissions, has not yet been measured. In order to summarize the available information, we use a virtual pastoral farm, with characteristics and management practices obtained from a real farm, Kapiti Research Station in Kenya. For outlining N flows at this virtual farm, we used published data, data from global studies, satellite imagery and geographic information system (GIS) tools. Our results show that N inputs in pastoral systems are dominated by atmospheric N deposition (˜80%), while inputs due to biological nitrogen fixation seems to play a smaller role. A major N loss pathway is nitrogen leaching (nitrate > DON) from pastures (33%). Cattle enclosures (bomas), where animals are kept during night, represent N emissions hotspots, representing 16% of the total N losses from the system. N losses via ammonia volatilization and N2O were four and three orders of magnitude higher from bomas than from the pasture, respectively. Based on our results, we further identify future research requirements and highlight the urgent need for experimental data collection to quantify nitrogen losses from manure in animal congregation areas. Such information is needed to improve our understanding on N cycling in pastoral systems in semiarid regions and to provide practical recommendations for managers that can help with decision‐making on management strategies in pastoral systems in semiarid savannas.

Abstract There is an urgent need for standardized monitoring of existing soil organic carbon stocks in order to accurately quantify potential negative or positive feedbacks with climate change on carbon fluxes. Given the uncertainty of flux measurements at the ecosystem scale, obtaining precise estimates of changes in soil organic carbon stocks is essential to provide an independent assessment of long-term net ecosystem carbon exchange. Here we describe the standard procedure to monitor the soil organic carbon stocks within the footprint of an eddy covariance flux tower, as applied at ecosystem stations of the Integrated Carbon Observation System. The objectives are i) to ensure comparability between sites and to be able to draw general conclusions from the results obtained across many ecosystems and ii) to optimize the sampling design in order to be able to prove changes in time using a reduced number of samples. When sampling a given site at two periods, the objective is generally to assess if changes occurred in time. The changes that can be detected (i.e., demonstrated as statistically significant) depend on several parameters such as the number of samples, the spatial sampling design, and the inherent within-site soil variability. Depending on these parameters, one can define the ‘minimum detectable change’ which is the minimum value of changed that can be statistically proved. Using simulation studies, we address the trade-off between increasing the number of samples and getting lower minimum detectable changes of soil organic carbon stocks.