Methane (CH₄) emissions from natural landscapes constitute roughly half of global CH₄ contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH₄ flux are ideal for constraining ecosystem-scale CH₄ emissions due to quasi-continuous and high-temporal-resolution CH₄ flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH₄ Version 1.0, the first open-source global dataset of CH₄ EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH₄ includes half-hourly and daily gap-filled and non-gap-filled aggregated CH₄ fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH₄ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH₄ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH₄ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH₄ fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH₄ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20^∘ S to 20^∘ N) the spring onset of elevated CH₄ emissions starts 3 d earlier, and the CH₄ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH₄ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH₄ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH₄ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH₄ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH₄ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH₄ peak). FLUXNET-CH₄ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH₄ cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH₄ data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

We test the relationship between canopy photosynthesis and reflected near‐infrared radiation from vegetation across a range of functional (photosynthetic pathway and capacity) and structural conditions (leaf area index, fraction of green and dead leaves, canopy height, reproductive stage, and leaf angle inclination), weather conditions, and years using a network of field sites from across central California. We based our analysis on direct measurements of canopy photosynthesis, with eddy covariance, and measurements of reflected near‐infrared and red radiation from vegetation, with light‐emitting diode sensors. And we interpreted the observed relationships between photosynthesis and reflected near‐infrared radiation using simulations based on the multilayer, biophysical model, CanVeg. Measurements of reflected near‐infrared radiation were highly correlated with measurements of canopy photosynthesis on half‐hourly, daily, seasonal, annual, and decadal time scales across the wide range of function and structure and weather conditions. Slopes of the regression between canopy photosynthesis and reflected near‐infrared radiation were greatest for the fertilized and irrigated C₄ corn crop, intermediate for the C₃ tules on nutrient‐rich organic soil and nitrogen fixing alfalfa, and least for the native annual grasslands and oak savanna on nutrient‐poor, mineral soils. Reflected near‐infrared radiation from vegetation has several advantages over other remotely sensed vegetation indices that are used to infer canopy photosynthesis; it does not saturate at high leaf area indices, it is insensitive to the presence of dead legacy vegetation, the sensors are inexpensive, and the reflectance signal is strong. Hence, information on reflected near‐infrared radiation from vegetation may have utility in monitoring carbon assimilation in carbon sequestration projects or on microsatellites orbiting Earth for precision agriculture applications.

The ability to accurately monitor and anticipate changes in consumptive water use associated with changing land use and land management is critical to developing sustainable water management strategies in water-limited climatic regions. In this paper, we present an application of a remote sensing data fusion technique for developing high spatiotemporal resolution maps of evapotranspiration (ET) at scales that can be associated with changes in land use. The fusion approach combines ET map timeseries developed using an multi-scale energy balance algorithm applied to thermal data from Earth observation platforms with high spatial but low temporal resolution (e.g., Landsat) and with moderate resolution but frequent temporal coverage (e.g., MODIS (Moderate Resolution Imaging Spectroradiometer)). The approach is applied over the Sacramento-San Joaquin Delta region in California—an area critical to both agricultural production and drinking water supply within the state that has recently experienced stresses on water resources due to a multi-year (2012–2017) extreme drought. ET “datacubes” with 30-m resolution and daily timesteps were constructed for the 2015–2016 water years and related to detailed maps of land use developed at the same spatial scale. The ET retrievals are evaluated at flux sites over multiple land covers to establish a metric of accuracy in the annual water use estimates, yielding root-mean-square errors of 1.0, 0.8, and 0.3 mm day⁻¹ at daily, monthly, and yearly timesteps, respectively, for all sites combined. Annual ET averaged over the Delta changed only 3 mm year⁻¹ between water years, from 822 to 819 mm year⁻¹, translating to an area-integrated total change in consumptive water use of seven thousand acre-feet (TAF). Changes were largest in areas with recorded land-use change between water years—most significantly, fallowing of crop land presumably in response to reductions in water availability and allocations due to the drought. Moreover, the time evolution in water use associated with wetland restoration—an effort aimed at reducing subsidence and carbon emissions within the inner Delta—is assessed using a sample wetland chronosequence. Region-specific matrices of consumptive water use associated with land use changes may be an effective tool for policymakers and farmers to understand how land use conversion could impact consumptive use and demand.

Peatland drainage is an important driver of global soil carbon loss and carbon dioxide (CO₂) emissions. Restoration of peatlands by reflooding reverses CO₂ losses at the cost of increased methane (CH₄) emissions, presenting a biogeochemical compromise. While restoring peatlands is a potentially effective method for sequestering carbon, the terms of this compromise are not well constrained. Here we present 14 site years of continuous CH₄ and CO₂ ecosystem‐scale gas exchange over a network of restored freshwater wetlands in California, where long growing seasons, warm weather, and managed water tables result in some of the largest wetland ecosystem CH₄ emissions recorded. These large CH₄ emissions cause the wetlands to be strong greenhouse gas sources while sequestering carbon and building peat soil. The terms of this biogeochemical compromise, dictated by the ratio between carbon sequestration and CH₄ emission, vary considerably across small spatial scales, despite nearly identical wetland climate, hydrology, and plant community compositions.