Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

N2O and CH4 fluxes from intensively managed grassland: The importance of biological and environmental drivers vs. management.

Agriculture is the main contributor to anthropogenic nitrous oxide (N2O) and methane (CH4) emissions. Therefore, mitigation options are urgently needed. In contrast to carbon dioxide, eddy covariance measurements of N2O and CH4 fluxes are still scarce, and thus little is known how environmental and biotic drivers as well as management affect the net N2O and CH4 exchange in grasslands. Thus, we investigated the most important drivers of net ecosystem N2O and CH4 fluxes in a temperate grassland, and continued a N2O mitigation experiment (increased clover proportion vs. fertilization with slurry). Random forest gap-filling models were able to capture intermittent emission peaks, performing better for half-hourly N2O than for CH4 fluxes. The unfertilized clover parcel (parcel B) continued to show lower N2O emissions (4.4 and 2.7 kg N2O-N ha-1 yr-1) compared to the fertilized parcel (parcel A; 6.9 and 5.9 kg N2O-N ha-1 yr-1) for 2019 and 2020, respectively. Tier 1 nitrogen (N) emission factors of 2.6 % and 1.9 % were observed at the fertilized parcel during the study period. Lower soil N concentrations indicated a lower N leaching risk at the clover than at the fertilized parcel. Annual CH4 emissions (including periods with sheep grazing) were similar from both parcels, and ranged from 25 to 38.5 kg CH4-C ha-1. The most important drivers of both N2O and CH4 fluxes were lagged precipitation and water filled pore space, but also management (for N2O from parcel B; CH4 from parcel A). Biotic variables such as vegetation height and leaf area index were important predictors for the N2O exchange, while grazing temporarily increased CH4 emissions. Overall, reducing N fertilization and increasing the legume proportion were effective N2O reduction measures. In particular, adjusting N fertilization to plant N demands can help to avoid high N2O emissions from grasslands.

Physiological response of Swiss ecosystems to 2018 drought across plant types and elevation.

Using five eddy covariance flux sites (two forests and three grasslands), we investigated ecosystem physiological responses to the 2018 drought across elevational gradients in Switzerland. Flux measurements showed that at lower elevation sites (below 1000 m.a.s.l.; grassland and mixed forest) annual ecosystem productivity (GPP) declined by approximately 20% compared to the previous 2 years (2016 and 2017), which led to a reduced annual net ecosystem productivity (NEP). At the high elevation sites, however, GPP increased by approximately 14% and as a result NEP increased in the alpine and montane grasslands, but not in the subalpine coniferous forest. There, increased ecosystem respiration led to a reduced annual NEP, despite increased GPP and lengthening of the growing period. Among all ecosystems, the coniferous forest showed the most pronounced negative stomatal response to atmospheric dryness (i.e. vapour pressure deficit, VPD) that resulted in a decline in surface conductance and an increased water-use efficiency during drought. While increased temperature enhanced the water-use efficiency of both forests, de-coupling of GPP from evapotranspiration at the low-elevation grassland site negatively affected water-use efficiency due to non-stomatal reductions in photosynthesis. Our results show that hot droughts (such as in 2018) lead to different responses across plants types, and thus ecosystems. Particularly grasslands at lower elevations are the most vulnerable ecosystems to negative impacts of future drought in Switzerland. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.