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.

The response of evapotranspiration (ET) to warming is of critical importance to the water and carbon cycle of the boreal biome, a mosaic of land cover types dominated by forests and peatlands. The effect of warming-induced vapour pressure deficit (VPD) increases on boreal ET remains poorly understood because peatlands are not specifically represented as plant functional types in Earth system models. Here we show that peatland ET increases more than forest ET with increasing VPD using observations from 95 eddy covariance tower sites. At high VPD of more than 2 kPa, peatland ET exceeds forest ET by up to 30%. Future (2091–2100) mid-growing season peatland ET is estimated to exceed forest ET by over 20% in about one-third of the boreal biome for RCP4.5 and about two-thirds for RCP8.5. Peatland-specific ET responses to VPD should therefore be included in Earth system models to avoid biases in water and carbon cycle projections.

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.

The latitudinal gradient of the start of the growing season (SOS) and the end of the growing season (EOS) were quantified in Alaska (61°N to 71°N) using satellite-based and ground-based datasets. The Alaskan evergreen needleleaf forests are sparse and the understory vegetation has a substantial impact on the satellite signal. We evaluated SOS and EOS of understory and tundra vegetation using time-lapse camera images. From the comparison of three SOS algorithms for determining SOS from two satellite datasets (SPOT-VEGETATION and Terra-MODIS), we found that the satellite-based SOS timing was consistent with the leaf emergence of the forest understory and tundra vegetation. The ensemble average of SOS over all satellite algorithms can be used as a measure of spring leaf emergence for understory and tundra vegetation. In contrast, the relationship between the ground-based and satellite-based EOSs was not as strong as that of SOS both for boreal forest and tundra sites because of the large biases between those two EOSs (19 to 26days). The satellite-based EOS was more relevant to snowfall events than the senescence of understory or tundra. The plant canopy radiative transfer simulation suggested that 84–86% of the NDVI seasonal amplitude could be a reasonable threshold for the EOS determination. The latitudinal gradients of SOS and EOS evaluated by the satellite and ground data were consistent and the satellite-derived SOS and EOS were 3.5 to 5.7daysdegree−1 and −2.3 to −2.7daysdegree−1, which corresponded to the spring (May) temperature sensitivity of −2.5 to −3.9days°C−1 in SOS and the autumn (August and September) temperature sensitivity of 3.0 to 4.6days°C−1 in EOS. This demonstrates the possible impact of phenology in spruce forest understory and tundra ecosystems in response to climate change in the warming Artic and sub-Arctic regions