Monitoring Natural Vegetation in Southern Greenland Using NOAA AVHRR and Field Measurements

The application of the Normalized Difference Vegetation Index (NDVI) for monitoring natural vegetation and biomass production has been evaluated for a sheep farming area in southern Greenland. Field measurements of spectral reflectance data during the growing season have been used to make a calibration between NOAA AVHRR NDVIs and aboveground vegetation quantities. The potential biomass production is estimated as the product of mean NDVI and the length of the growing season. Lowest-order atmospheric as well as geometric corrections were carried out on the satellite data before the seasonal and regional variations were correlated with climate and water balance. Agriculture in southern Greenland started when Eric the Red came from Iceland around 982 A.D., and the Norse era ended approximately 500 years later because of climatic change, extensive overgrazing and soil erosion. Modern sheep farming started in 1924, but the threats to sheep breeding and the environment are the same today as during the Norse era. The satellite-based monitoring has proved to be a useful tool to avoid overgrazing, which in this foehn-affected area easily implies soil erosion. It is a quick and low-cost method, and in combination with meteorological and soil water data it is possible to forecast the dry biomass production at the beginning of each growing season. This facilitates agricultural management and planning of the potential breeding capacity in this vulnerable marginal environment.Key words: southern Greenland, NOAA-AVHRR, Normalized Difference Vegetation Index, atmospheric corrections, biomass productionMots clés: Groenland méridional, radiomètre perfectionné à très haute résolution de la NOAA, indice de la végétation par différence normalisée, corrections atmosphériques, production de biomass

Deltas, freshwater discharge, and waves along the Young Sound, NE Greenland

A wide range of delta morphologies occurs along the fringes of the Young Sound in Northeast Greenland due to spatial heterogeneity of delta regimes. In general, the delta regime is related to catchment and basin characteristics (geology, topography, drainage pattern, sediment availability, and bathymetry), fluvial discharges and associated sediment load, and processes by waves and currents. Main factors steering the Arctic fluvial discharges into the Young Sound are the snow and ice melt and precipitation in the catchment, and extreme events like glacier lake outburst floods (GLOFs). Waves are subordinate and only rework fringes of the delta plain forming sandy bars if the exposure and fetch are optimal. Spatial gradients and variability in driving forces (snow and precipitation) and catchment characteristics (amount of glacier coverage, sediment characteristics) as well as the strong and local influence of GLOFs in a specific catchment impede a simple upscaling of sediment fluxes from individual catchments toward a total sediment flux into the Young Sound

Comparison of organic and conventional food and food production. Part II: Animal health and welfare in Norway

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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