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.

Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO₂ and CH₄ fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH₄ emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO₂ uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH₄ emissions for the benefit of net carbon sequestration. With a sustained pulse–response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH₄ emissions and cumulative CO₂ exchange. Significance Wetlands are unique ecosystems because they are in general sinks for carbon dioxide and sources of methane. Their climate footprint therefore depends on the relative sign and magnitude of the land–atmosphere exchange of these two major greenhouse gases. This work presents a synthesis of simultaneous measurements of carbon dioxide and methane fluxes to assess the radiative forcing of natural wetlands converted to agricultural or forested land. The net climate impact of wetlands is strongly dependent on whether they are natural or managed. Here we show that the conversion of natural wetlands produces a significant increase of the atmospheric radiative forcing. The findings suggest that management plans for these complex ecosystems should carefully account for the potential biogeochemical effects on climate.

We present 6.5 years of eddy covariance measurements of fluxes of methane (F_CH4) and carbon dioxide (F_CO2) from a flooded rice paddy in Northern California, USA. A pronounced warming trend throughout the study associated with drought and record high temperatures strongly influenced carbon (C) budgets and provided insights into biophysical controls of F_CO2 and F_CH4. Wavelet analysis indicated that photosynthesis (gross ecosystem production, GEP) induced the diel pattern in F_CH4, but soil temperature (T_s) modulated its amplitude. Forward stepwise linear models and neural networking modeling were used to assess the variables regulating seasonal F_CH4. As expected due to their competence in modeling nonlinear relationships, neural network models explained considerably more of the variance in daily average F_CH4 than linear models. During the growing season, GEP and water levels typically explained most of the variance in daily average F_CH4. However, T_s explained much of the interannual variability in annual and growing season CH₄ sums. Higher T_s also increased the annual and growing season ratio of F_CH4 to GEP. The observation that the F_CH4 to GEP ratio scales predictably with T_s may help improve global estimates of F_CH4 from rice agriculture. Additionally, T_s strongly influenced ecosystem respiration, resulting in large interannual variability in the net C budget at the paddy, emphasizing the need for long‐term measurements particularly under changing climatic conditions.

Methane (CH₄) exchange in wetlands is complex, involving nonlinear asynchronous processes across diverse time scales. These processes and time scales are poorly characterized at the whole‐ecosystem level, yet are crucial for accurate representation of CH₄ exchange in process models. We used a combination of wavelet analysis and information theory to analyze interactions between whole‐ecosystem CH₄ flux and biophysical drivers in two restored wetlands of Northern California from hourly to seasonal time scales, explicitly questioning assumptions of linear, synchronous, single‐scale analysis. Although seasonal variability in CH₄ exchange was dominantly and synchronously controlled by soil temperature, water table fluctuations, and plant activity were important synchronous and asynchronous controls at shorter time scales that propagated to the seasonal scale. Intermittent, subsurface water table decline promoted short‐term pulses of methane emission but ultimately decreased seasonal CH₄ emission through subsequent inhibition after rewetting. Methane efflux also shared information with evapotranspiration from hourly to multiday scales and the strength and timing of hourly and diel interactions suggested the strong importance of internal gas transport in regulating short‐term emission. Traditional linear correlation analysis was generally capable of capturing the major diel and seasonal relationships, but mesoscale, asynchronous interactions and nonlinear, cross‐scale effects were unresolved yet important for a deeper understanding of methane flux dynamics. We encourage wider use of these methods to aid interpretation and modeling of long‐term continuous measurements of trace gas and energy exchange.

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