The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The 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.Peer reviewe

Recent dynamics of forest fires in Quercus suber stands in Sardinia, Corsica and Catalonia

International audienc

Fuel type characterization and potential fire behavior estimation in Sardinia and Corsica islands

Wildland fires represent a serious threat to forests and wooded areas of the Mediterranean Basin. As recorded by the European Commission (2009), during the last decade Southern Countries have experienced an annual average of about 50,000 forest fires and about 470,000 burned hectares. The factor that can be directly manipulated in order to minimize fire intensity and reduce other fire impacts, such as three mortality, smoke emission, and soil erosion, is wildland fuel. Fuel characteristics, such as vegetation cover, type, humidity status, and biomass and necromass loading are critical variables in affecting wildland fire occurrence, contributing to the spread, intensity, and severity of fires. Therefore, the availability of accurate fuel data at different spatial and temporal scales is needed for fire management applications, including fire behavior and danger prediction, fire fighting, fire effects simulation, and ecosystem simulation modeling. In this context, the main aims of our work are to describe the vegetation parameters involved in combustion processes and develop fire behavior fuel maps. The overall work plan is based firstly on the identification and description of the different fuel types mainly affected by fire occurrence in Sardinia (Italy) and Corsica (France) Islands, and secondly on the clusterization of the selected fuel types in relation to their potential fire behavior. In the first part of the work, the available time series of fire event perimeters and the land use map data were analyzed with the purpose of identifying the main land use types affected by fires. Thus, field sampling sites were randomly identified on the selected vegetation types and several fuel variables were collected (live and dead fuel load partitioned following Deeming et al., (1977), depth of fuel layer, plant cover, surface area-to-volume ratio, heat content). In the second part of the work, the potential fire behavior for every experimental site was simulated using BEHAVE fire behavior prediction system (Andrews, 1989) and experimental fuel data. Fire behavior was simulated by setting different weather scenarios representing the most frequent summer meteorological conditions. The simulation outputs (fireline intensity, rate of spread, flame length) were then analyzed for clustering the different fuel types in relation to their potential fire behavior. The results of this analysis can be used to produce fire behavior fuel maps that are important tools in evaluating fire hazard and risk for land management planning, locating and rating fuel treatments, and aiding in environmental assessments and fire danger programs modeling

iRhom2 regulates ectodomain shedding and surface expression of the major histocompatibility complex (MHC) class I

Proteolytic release of transmembrane proteins from the cell surface, the so called ectodomain shedding, is a key process in inflammation. Inactive rhomboid 2 (iRhom2) plays a crucial role in this context, in that it guides maturation and function of the sheddase ADAM17 (a disintegrin and metalloproteinase 17) in immune cells, and, ultimately, its ability to release inflammatory mediators such as tumor necrosis factor alpha (TNF alpha). Yet, the macrophage sheddome of iRhom2/ADAM17, which is the collection of substrates that are released by the proteolytic complex, is only partly known. In this study, we applied high-resolution proteomics to murine and human iRhom2-deficient macrophages for a systematic identification of substrates, and therefore functions, of the iRhom2/ADAM17 proteolytic complex. We found that iRhom2 loss suppressed the release of a group of transmembrane proteins, including known (e.g. CSF1R) and putative novel ADAM17 substrates. In the latter group, shedding of major histocompatibility complex class I molecules (MHC-I) was consistently reduced in both murine and human macrophages when iRhom2 was ablated. Intriguingly, it emerged that in addition to its shedding, iRhom2 could also control surface expression of MHC-I by an undefined mechanism. We have demonstrated the biological significance of this process by using an in vitro model of CD8+ T-cell (CTL) activation. In this model, iRhom2 loss and consequent reduction of MHC-I expression on the cell surface of an Epstein-Barr virus (EBV)-transformed lymphoblastoid cell line dampened activation of autologous CTLs and their cell-mediated cytotoxicity. Taken together, this study uncovers a new role for iRhom2 in controlling cell surface levels of MHC-I by a dual mechanism that involves regulation of their surface expression and ectodomain shedding

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Abstract The 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

Reprints and permissions:

sagepub.co.uk/journalsPermissions.na