Planned changes to land use in West Africa have been proposed to both combat desertification and to preserve biodiversity in the region, however, there is an urgent need for tools to assess the effects of these proposed changes on local and regional scale precipitation. We use a high-resolution, convection-permitting numerical weather prediction (NWP) model to study how the initiation and propagation of mesoscale convective systems (MCS) depends on the surface vegetation cover. The simulations covered a 4-day period during the West African monsoon in August 2006.

Soil erosion in terrestrial ecosystems, as an important global environmental problem, significantly impacts on environmental quality and social economy. By protecting soil from wind and water erosion, terrestrial ecosystems supply human beings with soil erosion control service, one of the fundamental ecosystem services that ensure human welfare. The Loess Plateau was one of the regions in the world that suffered from severe soil erosion. In the past decades, restoration projects were implemented to improve soil erosion control in the region.

Using the UNFCCC as a basis, and the objectives of estimating soil organic carbon (SOC) changes during the period 1900–2100, a spatially explicit database of climate, land cover and soil texture was compiled for a 262,000 km2 region in semi-arid Sudan. The area is characterized by low input cultivation of millet, sorghum and sesamé combined with livestock grazing. By integrating the database with the CENTURY ecosystem model, we were able to estimate historical, current and future pools of SOC as a function of land management and climate.

Memory is among the most important and neglected forces that shapes animal movement patterns. Research on the movement–memory interface is crucial to understand how animals use spatial learning to navigate across space because memory‐based navigation is directly linked to animals' space use and home range behaviour; however, because memory cannot be measured directly, it is difficult to account for. Here, we incorporated spatial memory into step selection functions (SSF) to understand how resource selection and spatial memory affect space use of feral hogs (Sus scrofa).

Three global datasets, the History Database of the Global Environment (HYDE), Kaplan and Krumhardt (KK) and Pongratz of reconstructed anthropogenic land cover change (ALCC) were introduced and compared in this paper. The HYDE dataset was reconstructed by Goldewijk and his colleagues at the National Institute of Public Health and the Environment in Netherland, covering the past 12 000 years. The KK dataset was reconstructed by Kaplan and his colleagues, the Soil-Vegetation-Atmosphere Research Group at the Institute of Environmental Engineering in Switzerland, covering the past 8000 years.

Soil organic carbon (SOC) constitutes a large pool within the global carbon cycle. Land use change significantly drives SOC stock variation. In tropical central and eastern Africa, how changes in land use and land cover impact on soil C stocks remains unclear. Variability in the existing data is typically explained by soil and climate factors with little consideration given to land use and management history.

A remote-sensing and geographical information sysytem (GIS)-based quantitative methodology for landslide-susceptibility zonation is described in a stepwise manner with its application in the Igo River Basin in the West Siang District of Arunachal Pradesh, Eastern Himalaya, India. Parameters such as geology, physiography, slope angle, slope length, slope aspect, slope type, generic landforms, lineament distance, road distance, drainage distance, altitudinal zones and land cover are used for landslide-susceptibility zonation.

Changes in the spatial distribution of land cover and land use can have significant impacts on ecological processes at multiple scales; estimating these changes provides critical data for both monitoring and understanding land-use effects on these processes. One approach to mapping landcover changes, particularly useful over longer periods of time, is comparison of existing landcover maps, (post-classification change analysis).

Many ongoing processes in today's landscapes impact our environment considerably. Thus, it is enormously important to gather information on qualitative characteristics of our landscapes in order to effectively counteract the negative developments. Structural functionality as proxy for the assessment of habitat quality and species patterns has already proven potential to successfully describe ecological values.

Relationships between behavioral regulation, environmental temperatures, and physiological tolerance are critical to conservation policy; however, these relationships may not be consistent among sister taxa. A species geographic range is influenced by various factors including physiological tolerance to temperature change. In this study, we investigated the effects of temperature variation on thermal preference and standard metabolic rates (SMR) of two species of larval salamanders, Eurycea cirrigera (Southern Two-Lined Salamander) and Eurycea wilderae (Blue Ridge Two-Lined Salamander).

Land cover and vegetation change are among the most important aspects of environmental change. Vegetation change can be quantified by landscape pattern indices (LPI). Landscape indices are routinely calculated using planar land use/land cover (LU/LC) maps, obtained by the projection of a non-flat landscape surface into a two-dimensional Cartesian space. Especially in mountainous areas, quantification on planar maps can lead to underestimation of vegetation and land cover changes. Hoechstetter et al.

AIM: Spatial environmental heterogeneity (EH) is an important driver of species richness, affecting species coexistence, persistence and diversification. EH has been widely studied in ecology and evolution and quantified in many different ways, with a strong bias towards a few common measures of EH like elevation range. Here, we calculate 51 measures of EH within grid cells world‐wide across three spatial grains to investigate similarities and differences among these measures.