Advanced monitoring of crop traits with hyperspectral and multispectral time series

Crop rotations with legumes and use of organic and mineral fertilizers show potential to reduce agricultural N losses. This study examined N losses, including direct N₂ flux, on two adjacent sites with different management histories: organic farming (OF) with legume cultivation and integrated farming (IF) using synthetic and organic N inputs. IF increased soil organic carbon and nitrogen content and ¹⁵N recovery and showed a balanced N budget (i.e. more efficient N cycling compared to OF).

Grasslands shape the landscape in many parts of the world and serve as the main source of fodder for livestock. There is a lack of comprehensive data on grassland yield, although these data are highly valuable for authorities and research. By applying three approaches to estimate grassland yields, namely, a satellite data model, a biogeochemical model and a field measurements approach, we provide annual grassland yield maps for the Ammer region in 2019 and highlight the potentials and limitations of the approaches.

Research on methane emissions from African livestock is limited. We used a probabilistic method fusing drone and flux tower observations with an atmospheric model to estimate emissions from various herds. This approach proved robust under non-stationary wind conditions and effective in estimating emissions as low as 100 g h^-1. We also detected spectral anomalies in satellite data associated with the herds. Our method can be used for diverse point sources, thereby improving emission inventories.

The increase in atmospheric concentrations of several greenhouse gases (GHGs) since 1750 is attributed to human activity. However, natural ecosystems, such as tropical forests, also contribute to GHG budgets. The Congo Basin hosts the second largest tropical forest and is understudied. In this study, measurements of soil GHG exchange were carried out during 16 months in a tropical forest in the Congo Basin. Overall, the soil acted as a major source of CO₂ and N₂O and a minor sink of CH₄.

We applied a biogeochemical model on grasslands in the pre-Alpine Ammer region in Germany and analyzed the influence of soil and climate on annual yields. In drought affected years, total yields were decreased by 4 %. Overall, yields decrease with rising elevation, but less so in drier and hotter years, whereas soil organic carbon has a positive impact on yields, especially in drier years. Our findings imply, that adapted management in the region allows to mitigate yield losses from drought.

Agricultural landscapes act as sinks or sources of the greenhouse gases (GHGs) CO₂, CH₄, or N₂O. Various physicochemical and biological processes control the fluxes of these GHGs between ecosystems and the atmosphere. Therefore, fluxes depend on environmental conditions such as soil moisture, soil temperature, or soil parameters, which result in large spatial and temporal variations of GHG fluxes. Here, we describe an example of how this variation may be studied and analyzed.

Despite occupying <1 %; of the globe, streams are significant sources of greenhouse gas (GHG) emissions. In this study, we determined anthropogenic effects on GHG emissions from streams. We found that anthropogenic-influenced streams had up to 20 times more annual GHG emissions than natural ones and were also responsible for seasonal peaks. Anthropogenic influences also altered declining GHG flux trends with stream size, with potential impacts on stream-size-based spatial upscaling techniques.

The increase in global and regional temperatures has the potential to drive accelerated soil organic carbon losses in tropical forests. We simulated climate warming by translocating intact soil cores from higher to lower elevations. The results revealed increasing temperature sensitivity and decreasing losses of soil organic carbon with increasing elevation. Our results suggest that climate warming may trigger enhanced losses of soil organic carbon from tropical montane forests.

In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.

Actual maps of grassland traits could improve local farm management and support environmental assessments. We developed, assessed, and applied models to estimate dry biomass and plant nitrogen (N) concentration in pre-Alpine grasslands with drone-based multispectral data and canopy height information. Our results indicate that machine learning algorithms are able to estimate both parameters but reach a better level of performance for biomass.

Turbulent flux measurements suffer from a general systematic underestimation. One reason for this bias is non-local transport by large-scale circulations. A recently developed model for this additional transport of sensible and latent energy is evaluated for three different test sites. Different options on how to apply this correction are presented, and the results are evaluated against independent measurements.