The primary aim of the study was to estimate the spatial scale of pollen dispersal and deposition for pollen assemblages from moss polsters in the cultivated landscape of southern Sweden, as a mean to improve future studies of the pollen/vegetation relationship in the region, and interpretation of fossil pollen data in terms of past cultural landscapes. This can be done by estimating the ‘relevant source area of pollen’ (RSAP) defined as the area around the pollen sampling point beyond which the pollen-vegetation relationship does not improve. Forty-two sites from nonfertilized grasslands in the traditional open agricultural (Open Region) and semi-open forested (Semi-Open Region) regions of southern Sweden were selected. The vegetation survey was performed within a 1500 m radius area around the moss polsters sampling area. The extended R-value (ERV) model was used to evaluate the pollen-plant abundance relationship. The RSAP for moss polsters in the Open Region was estimated to c. 400 m from empirical data. In the Semi-Open Region, however, the likelihood function score, an indicator of the goodness-of-fit of the data to the ERV model, showed an unexpected pattern of change, making it difficult to evaluate the RSAP. Simulations using hypothetical landscapes suggest that systematic selection of sampling sites could cause this pattern. Simulations also demonstrate that the size of vegetation patches affect the RSAP, i.e., the larger the vegetation patches are, the larger the RSAP becomes. Similar RSAP for the Open and Semi-Open Regions is obtained in simulations using the same patch size, and random selection. In the actual vegetation, patch size is comparable in the two regions, which would suggest that the RSAP for moss polsters in the Semi-Open Region is c. 400 m as well.

In this study, we present a newly developed method for the estimation of surface flow paths on a digital elevation model (DEM). The objective is to use a form-based algorithm, analyzing flow over single cells by dividing them into eight triangular facets and to estimate the surface flow paths on a raster DEM. For each cell on a gridded DEM, the triangular form-based multiple flow algorithm (TFM) was used to distribute flow to one or more of the eight neighbor cells, which determined the flow paths over the DEM. Because each of the eight facets covering a cell has a constant slope and aspect, the estimations of -for example -flow direction and divergence/convergence are more intuitive and less complicated than many traditional raster-based solutions. Experiments were undertaken by estimating the specific catchment area (SCA) over a number of mathematical surfaces, as well as on a real-world DEM. Comparisons were made between the derived SCA by the TFM algorithm with eight other algorithms reported in the literature. The results show that the TFM algorithm produced the closest outcomes to the theoretical values of the SCA compared with other algorithms, derived more consistent outcomes, and was less influenced by surface shapes. The real-world DEM test shows that the TFM was capable of modeling flow distribution without noticeable 'artefacts', and its ability to track flow paths makes it an appropriate platform for dynamic surface flow simulation.

Urban flooding is of growing concern due to increasing densification of urban areas, changes in land use, and climate change. The traditional engineering approach to flooding is designing single-purpose drainage systems, dams, and levees. These methods, however, are known to increase the long-term flood risk and harm the riverine ecosystems in urban as well as rural areas. In the present paper, we depart from resilience theory and suggest a concept to improve urban flood resilience. We identify areas where contemporary challenges call for improved collaborative urban flood management. The concept emphasizes resiliency and achieved synergy between increased capacity to handle stormwater runoff and improved experiential and functional quality of the urban environments. We identify research needs as well as experiments for improved sustainable and resilient stormwater management namely, flexibility of stormwater systems, energy use reduction, efficient land use, priority of transport and socioeconomic nexus, climate change impact, securing critical infrastructure, and resolving questions regarding responsibilities.

Socio-economic shocks, technogenic catastrophes, and armed conflicts often have drastic impacts on local and regional food security through disruption of agricultural production and food trade, reduced investments, and deterioration of land and infrastructure. Recently, more research has focused on the effects of armed conflict on land systems, but still little is known about the processes and outcomes of such events. Here we use the case of Syria and Iraq and the seizure of land by the Islamic State (IS) since 2014 as an example of armed conflict, where we investigate the effects on agricultural land use. We apply a reproducible approach using 250 m satellite-based time-series data to quantify the areas under cultivation from 2000 to 2015. Despite a common belief about widespread land abandonment in areas under conflict, results point to multiple trajectories regarding cropland cultivation in the IS seized area: (1) expansion of cropland to formerly un-cultivated areas, (2) cropland abandonment, and (3) decrease of high-intensity cropland. Our study highlights the need to understand these diverse conflict-related and contextdependent changes to the land system.

Spatial ecology focuses on the role of space and time in ecological processes and events from a local to a global scale and is particularly relevant in developing environmental policy and (mandated) monitoring goals. In other words, spatial ecology is where geography and ecology intersect, and high-quality geospatial data and analysis tools are required to address emerging issues in spatial ecology. In this commentary and review for the International Journal of GIS Special Issue on Spatial Ecology, we highlight selected current research priorities in spatial ecology and describe geospatial data and methods for addressing these tasks. Geoinformation research themes are identified in population ecology, community and landscape ecology, and ecosystem ecology, and these themes are further linked to the assessment of ecosystem services. Methods in spatial ecology benefit from explicit consideration of spatial autocorrelation, and applications discussed in this review include species distribution modeling, remote sensing of community and ecosystem properties, and models of climate change. The linkages of the Special Issue papers to these emerging issues are described.