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Today societies face an unprecedented challenge to limit global warming and restore agricultural soils. Recent studies show that the introduction of cover crops over Europe could result in a cooling impact due to an increase in soil organic carbon stocks, a decrease in the use of fertilizers, and an increase in surface albedo of the croplands. Based on the use of remote sensing data, land cover database, meteorological data, national agricultural statistics, and ground measurements, a generic model was developed to simulate the radiative forcing following the change in surface albedo. This article analyzes the impact of the introduction of cover crops in Europe during the fallow periods. Compared to previous studies, this work discusses: (i) The maximum greening potential in Europe and the associated indirect surface properties changes (ii) for snowfall episodes, and (iii) due to an increase in organic matter. This study shows that the mitigation potential of cover crops through albedo effects could reach 6.74 MtCO2-eq.yr−1 by extending the periods of the introduction of the cover crops to all possible fallow periods. This mitigation could be limited to 5.68 MtCO2-eq.yr−1 if the impact of snowfalls is considered. This would be equivalent to 9.12 gCO2.m−2.yr−1. Finally, this study investigates the feedback loop due to soil darkening with soil organic carbon content increase when cover crops are introduced, considering two scenarios. The first considers the soil organic carbon content increase following repeated incorporation of cover crop biomass into the soil, simulated with the DayCent model. The second, more conceptual and extreme scenario aims at alerting on the possible impact of a combination of carbon farming practices, such as biochar or organic amendments. Our results show that this effect could lead to a loss of 20% of the climate benefit (i.e., 5.39 MtCO2-eq.yr−1). In conclusion, this study shows that cover crops have a strong potential for climate mitigation through direct albedo effects (soil coverage). However, once introduced, cropland should be permanently covered by vegetation or straws in order to avoid this darkening feedback loop effect. [ABSTRACT FROM AUTHOR]

Wetlands are a critical component of the landscape for climate mitigation, adaptation, biodiversity, and human health and prosperity. Keeping an eye on wetland vegetation is crucial due to it playing a major role in the planet's carbon cycle and ecosystem management. By measuring the chlorophyll fluorescence (ChF) emitted by plants, we can get a precise understanding of the current state and photosynthetic activity. In this study, we applied the Extreme Gradient Boost (XGBoost) algorithm to map ChF in the Biebrza Valley, which has a unique ecosystem in Europe for peatlands, as well as highly diversified flora and fauna. Our results revealed the advantages of using a set of classifiers derived from EO Sentinel-2 (S-2) satellite image mosaics to accurately map the spatio-temporal distribution of ChF in a terrestrial landscape. The validation proved that the XGBoost algorithm is quite accurate in estimating ChF with a good determination of 0.71 and least bias of 0.012. The precision of chlorophyll fluorescence measurements is reliant upon determining the optimal S-2 satellite overpass time, which is influenced by the developmental stage of the plants at various points during the growing season. Finally, the model performance results indicated that biophysical factors are characterized by greenness- and leaf-pigment-related spectral indices. However, utilizing vegetation indices based on extended periods of remote sensing data that better capture land phenology features can improve the accuracy of mapping chlorophyll fluorescence. [ABSTRACT FROM AUTHOR]

Today, European forests face many challenges but also offer opportunities, such as climate change mitigation, provision of renewable resources, energy and other ecosystem services. Large-scale analyses to assess these opportunities are hindered by the lack of a consistent, spatial and accessible forest structure data. This study presents a freely available pan-European forest structure data set. Building on our previous work, we used data from six additional countries and consider now ten key forest stand variables. Harmonized inventory data from 16 European countries were used in combination with remote sensing data and a gap-filling algorithm to produce this consistent and comparable forest structure data set across European forests. We showed how land cover data can be used to scale inventory data to a higher resolution which in turn ensures a consistent data structure across sub-regional, country and European forest assessments. Cross validation and comparison with published country statistics of the Food and Agriculture Organization (FAO) indicate that the chosen methodology is able to produce robust and accurate forest structure data across Europe, even for areas where no inventory data were available. [ABSTRACT FROM AUTHOR]