L. Claessens

Landsliding and Its Multiscale Influence on Mountainscapes

Landsliding is a complex process that modifies mountainscapes worldwide. Its severe and sometimes long-lasting negative effects contrast with the less-documented positive effects on ecosystems, raising numerous questions about the dual role of landsliding, the feedbacks between biotic and geomorphic processes, and, ultimately, the ecological and evolutionary responses of organisms. We present a conceptual model in which feedbacks between biotic and geomorphic processes, landslides, and ecosystem attributes are hypothesized to drive the dynamics of mountain ecosystems at multiple scales. This model is used to integrate and synthesize a rich, but fragmented, body of literature generated in different disciplines, and to highlight the need for profitable collaborations between biologists and geoscientists. Such efforts should help identify attributes that contribute to the resilience of mountain ecosystems, and also should help in conservation, restoration, and hazard assessment. Given the sensitivity of mountains to land-use and global climate change, these endeavors are both relevant and timely.

Contribution of Topographically Based Landslide Hazard Modelling to the Analysis of the Spatial Distribution and Ecology of Kauri (Agathis australis)

In this paper the use of topographical attributes for the analysis of the spatial distribution and ecological cycle of kauri (Agathis australis), a canopy emergent conifer tree from northern New Zealand, is studied. Several primary and secondary topographical attributes are derived from a Digital Elevation Model (DEM) for a study area in the Waitakere Ranges. The contribution of these variables in explaining presence or absence of mature kauri is assessed with logistic regression and Receiver Operating Characteristic (ROC) plots. A topographically based landslide hazard index, calculated by combining a steady state hydrologic model with the infinite slope stability equation, appears to be very useful in explaining the occurrence and ecological dynamics of kauri. It is shown that the combination of topographical, soil physical and hydrological parameters in the calculation of this single landslide hazard index, performs better in explaining presence of mature kauri than using topographical attributes calculated from the DEM alone. Moreover, this study demonstrates the possibilities of using terrain attributes for representing geomorphological processes and disturbance mechanisms, often indispensable in explaining a species’ ecological cycle. The results of this analysis support the ‘temporal stand replacement model’, involving disturbance as a dominant ecological process in forest regeneration, as an interpretation of the community dynamics of kauri. Furthermore a threshold maturity stage, in which trees become able to stabilize landslide prone sites and postpone a possible disturbance, together with great longevity are seen as major factors making kauri a ‘landscape engineer’.

Chapter 5 Geostatistical Simulation and Error Propagation in Geomorphometry

Publisher Summary This chapter aims to demonstrate how uncertainty in digital elevation model (DEM) attributes can be quantified using geostatistical methods and to show how the propagation of errors to DEM derived products may be computed. To attribute errors DEMs may have positional errors like a shift along one or both coordinate axes, rotational errors, scaling errors, projection errors, or a combination of these. In this chapter, only attribute errors are considered. It describe how propagation of attribute errors in spatial modeling can be computed using the Monte-Carlo method. This method is the most often used error propagation method because it is generic, flexible, and intuitively appealing. In order of increasing complexity, the chapter considers the propagation of error from DEMs to three derivatives, namely slope (a local land-surface parameter), topographic wetness index (a regional land-surface parameter), and soil redistribution resulting from water erosion (a complex model). It also describes the uncertainty propagation analysis in detail.

Makers and Users of Geomorphological Maps

Abstract In the last 60 years, geomorphology has been recognised as an important field serving several other professions. At the same time there are still limited resources spent on either national or regional geomorphological mapping programmes compared to geological, soil, land cover mapping programmes. From the makers point of view, interesting exceptions in Europe are, for instance, the German, Austrian, Dutch, Spanish, and Italian national geomorphological mapping programmes. From the users point of view, one of the strongest supporters of applied geomorphological mapping is the British Engineering Geological Community that has understood the added value of engineering geomorphological mapping and the economic savings in project developments when this practice is in place. In this scenario, it is the private sector – for instance the insurance sector – and the ecological community that have the highest potential of upscaling geomorphological mapping efforts. We review existing national geomorphological mapping efforts and further develop the needs of geomorphological mapping in natural hazards zonation and landscape planning.

Crop-Livestock Intensification in the Face of Climate Change: Exploring Opportunities to Reduce Risk and Increase Resilience in Southern Africa Using an Integrated Multi-Modeling Approach

The climate of Southern Africa is highly variable at most time-scales and follows a pronounced gradient with arid conditions in the west and humid conditions in the east. There is also a marked latitudinal rainfall distribution pattern, with the southern part having a low rainfall index and high variability and the northern part having higher annual rainfall and lower interannual variability (Kandji et al., 2006). Over the last 100 years, temperatures have increased by about 0.5◦C in the region and downward trends in rainfall have also occurred (Kandji et al., 2006; Morton, 2007). There has also been an increase in drought eventswith over 15 drought events reported in the region between 1988 and 1992. The frequency and intensity of El Nin˜o episodes have increased. Prior to the 1980s, strong El Nin˜o events occurred every 10–20 years; between 1980 and 2000, the region experienced five episodes with the 1982–1983 and 1997–1998 episodes being the most intense of the century (Reason and Jagadheesha, 2005; Rouault and Richard, 2005). These episodes have contributed to stagnant or decreasing agricultural production and worsening food insecurity in the region (Kandji et al., 2006). Unfavorable climatic conditions and projected climate change are among the major obstacles to achieving food security in the region and also have dire consequences for macro-economic performance.

Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan Africa

In rainfed crop production, root zone plant-available water holding capacity (RZ-PAWHC) of the soil has a large influence on crop growth and the yield response to management inputs such as improved seeds and fertilisers. However, data are lacking for this parameter in sub-Saharan Africa (SSA). This study produced the first spatially explicit, coherent and complete maps of the rootable depth and RZ-PAWHC of soil in SSA. We compiled geo-referenced data from 28,000 soil profiles from SSA, which were used as input for digital soil mapping (DSM) techniques to produce soil property maps of SSA. Based on these soil properties, we developed and parameterised (pedotransfer) functions, rules and criteria to evaluate soil water retention at field capacity and wilting point, the soil fine earth fraction from coarse fragments content and, for maize, the soil rootability (relative to threshold values) and rootable depth. Maps of these secondary soil properties were derived using the primary soil property maps as input for the evaluation rules and the results were aggregated over the rootable depth to obtain a map of RZ-PAWHC, with a spatial resolution of 1 km2. The mean RZ-PAWHC for SSA is 74 mm and the associated average root zone depth is 96 cm. Pearson correlation between the two is 0.95. RZ-PAWHC proves most limited by the rootable depth but is also highly sensitive to the definition of field capacity. The total soil volume of SSA potentially rootable by maize is reduced by one third (over 10,500 km3) due to soil conditions restricting root zone depth. Of these, 4800 km3 are due to limited depth of aeration, which is the factor most severely limiting in terms of extent (km2), and 2500 km3 due to sodicity which is most severely limiting in terms of degree (depth in cm). Depth of soil to bedrock reduces the rootable soil volume by 2500 km3, aluminium toxicity by 600 km3, porosity by 120 km3 and alkalinity by 20 km3. The accuracy of the map of rootable depth and thus of RZ-PAWHC could not be validated quantitatively due to absent data on rootability and rootable depth but is limited by the accuracy of the primary soil property maps. The methodological framework is robust and has been operationalised such that the maps can easily be updated as additional data become available.

Mass-Movement Causes: Changes in Slope Angle

This chapter discusses and illustrates how changes in slope angle can cause mass movement. Several processes can cause removal of lateral or underlying support of a slope, and most of the time multiple processes are acting together on a landscape. Slow and sudden processes causing changes in slope angle are differentiated, and several examples and illustrations of each are given. In addition, this chapter reviews current literature on landscape evolution modeling in which researchers try to incorporate these geomorphological processes in the analysis and simulation of current and future landscapes.

Beyond the plot: technology extrapolation domains for scaling out agronomic science

Ensuring an adequate food supply in systems that protect environmental quality and conserve natural resources requires productive and resource-efficient cropping systems on existing farmland. Meeting this challenge will be difficult without a robust spatial framework that facilitates rapid evaluation and scaling-out of currently available and emerging technologies. Here we develop a global spatial framework to delineate ‘technology extrapolation domains’ based on key climate and soil factors that govern crop yields and yield stability in rainfed crop production. The proposed framework adequately represents the spatial pattern of crop yields and stability when evaluated over the data-rich US Corn Belt. It also facilitates evaluation of cropping system performance across continents, which can improve efficiency of agricultural research that seeks to intensify production on existing farmland. Populating this biophysical spatial framework with appropriate socio-economic attributes provides the potential to amplify the return on investments in agricultural research and development by improving the effectiveness of research prioritization and impact assessment.

Kenya public weather processed by the Global Yield Gap Atlas project

The Global Yield Gap Atlas project (GYGA - http://yieldgap.org ) has undertaken a yield gap assessment following the protocol recommended by van Ittersum et. al. (van Ittersum et. al., 2013). One part of the activities consists of collecting and processing weather data as an input for crop simulation models in sub-Saharan African countries including Kenya. This publication covers weather data for 10 locations in Kenya. The project looked for good quality weather data in areas where crops are pre-dominantly grown. As locations with good public weather data are sparse in Africa, the project developed a method to generate weather data from a combination of observed and other external weather data. One locations holds actually measured weather data, the other 9 locations show propagated weather data. The propagated weather data consist on TRMM rain data (or NASA POWER if TRMM is not available) and NASA POWER Tmax, Tmin, and Tdew data corrected based on calibrations with short-term (<10 years) observed weather data. sources (Van Wart et.al. 2015).

Scoping climate change adaptation strategies for smallholder farmers in East Africa - a multi-dimensional, multi-scenario impact assessment

This chapter assesses the characteristics of current and future agricultural systems, land use, agricultural output, output price, cost of production, and farm and household size in response to climate change. This analysis also compared both current and projected future climate (2030), with and without adaptation, and for different socioeconomic scenarios (Representative Agricultural Pathways, RAPs) in two study areas in Kenya. A new approach to impact assessment, the Tradeoff Analysis Model for Multi-Dimensional Impact Assessment (TOA-MD) was adopted for this analysis, which simulated technology adoption and associated economic, environmental and social outcomes in a heterogeneous farm population for a regional impact assessment. These case studies yield new insights into the way that adaptation strategies could improve the livelihoods of smallholder farmers operating in the mixed crop-livestock systems in East Africa.This book emphasis the role of farm level adaptation as a key in developmental pathways that are challenged by climate risks in the semi-arid tropics of Asia and Africa. It throws light on key issues that arise in farm level impacts, adaptation and vulnerability to climate change and discusses Q2 methodological approaches undertaken in study domains of Asia and Africa. The book systematically describes the perceptions, aspirations as elicited/voiced by the farmers and identifies determinants of adaptation decisions. Chapters identify constraints and opportunities that are translated into indicative intervention recommendations towards climate resilient farm households in the semi-arid tropics of Asia and Africa. Furthermore, it discusses with evidences that contributes to the development of livelihood strategy for poor farmers in Asia (Bangladesh, India, Sri Lanka, Thailand, Vietnam and China) and Africa (Burkina Faso, Niger, Kenya and Ghana).