The Normalized Difference Vegetation Index (NDVI), has been increasingly used to capture spatiotemporal variations in cover factor (C) determination for erosion prediction on a larger landscape scale. However, NDVI-based C factor (C_ndvi) estimation per se is sensitive to various biophysical variables, such as soil condition, topographic features, and vegetation phenology. As a result, C_ndvi often results in incorrect values that affect the quality of soil erosion prediction. The aim of this study is to multi-temporally estimate C_ndvi values and compare the values with those of literature values (C_lit) in order to quantify discrepancies between C values obtained via NDVI and empirical-based methods. A further aim is to quantify the effect of biophysical variables such as slope shape, erodibility, and crop growth stage variation on C_ndvi and soil erosion prediction on an agricultural landscape scale. Multi-temporal Landsat 7, Landsat 8, and Sentinel 2 data, from 2013 to 2016, were used in combination with high resolution agricultural land use data of the Integrated Administrative and Control System, from the Uckermark district of north-eastern Germany. Correlations between C_ndvi and C_lit improved in data from spring and summer seasons (up to r = 0.93); nonetheless, the C_ndvi values were generally higher compared with C_lit values. Consequently, modelling erosion using C_ndvi resulted in two times higher rates than modelling with C_lit. The C_ndvi values were found to be sensitive to soil erodibility condition and slope shape of the landscape. Higher erodibility condition was associated with higher C_ndvi values. Spring and summer taken images showed significant sensitivity to heterogeneous soil condition. The C_ndvi estimation also showed varying sensitivity to slope shape variation; values on convex-shaped slopes were higher compared with flat slopes. Quantifying the sensitivity of C_ndvi values to biophysical variables may help improve capturing spatiotemporal variability of C factor values in similar landscapes and conditions.

In Europe and elsewhere, agri‐environmental schemes (AES) are designed to reduce agriculture's impacts on the environment. Designing effective schemes requires an understanding of the reasons that drive farmers' decisions whether to adopt AES. Currently, most insights come from individual case studies or structured surveys based on predefined questions. There is a paucity of studies that do not rely on rigid preconceptions about relevant behavioural factors while also offering a geographically and socio‐culturally broad perspective that can address the cultural and institutional context‐specificity of behavioural studies. Also, most studies focus on the adoption decision, while implementation decisions and their consequences for the ecological effectiveness of AES remain understudied. In this article, we present the results from semi‐structured farmer interviews conducted in five agricultural landscapes across Europe. The results are used to uncover reasons for AES adoption as well as the implications of AES implementation decisions for their ecological effectiveness. The main reason for AES adoption that was common across case study regions is the interplay of opportunity costs and payment levels, which has negative implications for the ecological effectiveness of AES as farmers prioritized marginal land or adopted non‐additional AES. Among reasons that vary across regions, tenure relations and the role of ecological reasoning stand out. We find that AES are unlikely to trigger broader shifts towards sustainable management but there is some potential for improvement, mainly by increasing the flexibility, spatial targeting and ecological ambition of the schemes. Read the freePlain Language Summaryfor this article on the Journal blog.

The rich species pool in semi-natural grasslands is associated with high spatial and temporal heterogeneity. This empirical study is one of the first to jointly analyze the response of orders, individual species and functional richness of arthropods to particular management practices and to linear landscape features, such as strips of grass and belts of trees. Mostly it was the less mobile, flightless taxa that were negatively affected by immediate disturbance caused by mowing. At a larger time-scale, grasslands managed by mowing once every year, and especially by a combined regime of mowing and grazing, supported the highest species richness of butterflies and beetles. Most functional diversity measures reached maximum values soon after mowing. Both strips of grass and belts of trees substantially affected the invertebrate community structure as the majority of taxa were positively associated with these linear features. Based on our results, we propose postponing mowing to later in the year, mowing in gradual stages, maintaining uncut strips primarily along permanent landscape features and establishing both strips of grass and belts of trees in submontane grassland environments.

The analysis of changes in landscape use and the related significance of some natural factors is examined in this paper, using three municipal cadastral areas in Moravia, Czech Republic. The relationships between changes in the use of the rural landscape and natural conditions were analyzed with the use of GIS tools and methods of canonical correspondence analysis (CCA). The CCA results showed a correlation between the selected natural factors and landscape changes, with the most significant factors being those of slope and altitude. The CCA models exhibited varying reliability in accounting for the extent of landscape changes related to topographical diversity of the territories. Natural conditions were more influential in periods with lower change dynamics and at the same time in areas with higher topographic heterogeneity. Although the results of the statistical analyses confirmed the significance of natural factors, only a part of land use changes could be explained by their influence. Socio-economic factors are apparently the main forces affecting landscape character and change

Concentrated surface run-off caused by torrential rain leads to the transport of sediments from soil erosion processes within catchment areas of critical points, which represents a basic component of flood risks. Clear identification of such critical points offers a basis for a suitable new strategy of threat mitigation, via both organizational and structural measures in catchment areas. Critical points are determined in places where generated paths of concentrated surface run-off cross given boundaries of built-up areas. The threshold values for the catchment area of a critical point were derived on the basis of hydrological calculations, field research, and the evaluation of hundreds of specific manifestations of damage in built-up areas for particular critical profiles. The characteristics were determined as follows: contributing area between 0.3 and 10 km², average slope more than 3.5%, and percentage of arable land more than 40%. Indicator F was determined for the distribution of the territory of the Czech Republic according to the risk of flooding. Knowledge of the existence of critical points enables the implementation of preventive measures, the evaluation of flood risk associated with the transport of sediment due to erosion processes, and the improvement of management measures in respective catchment areas, even before an event occurs. The proposed procedure outputs shall be reflected in spatial planning documentation, land consolidation, and catchment area management plans. Incorporation of critical points into open-access public web-maps can help with assessing the semi-quantitative expression of risk to built-up areas arising from the threat of local flooding.