Plant biomass represents a sink for atmospheric carbon dioxide, which is one of the most important greenhouse gases and which is assumed to contribute more than half of the global warming. Establishing tree plantations or perennial crops on degraded land is an effective way to reduce atmospheric carbon by building up terrestrial carbon stocks, not only in the living biomass, but also in the soil. By converting Imperata cylindrica grassland into tree plantations (Acacia mangium or oil palm), aboveground biomass carbon can be increased about 20-fold and below ground biomass carbon up to 8-fold, while soil carbon can almost be doubled.

Coffea arabica, one of the economically most important crops worldwide, occurs naturally in the undergrowth of montane rainforests of Ethiopia. The study provides the first detailed ecophysiological investigations of wild coffee populations. It demonstrates the inter- and intra-regional variability in phenotypic and hydrological characteristics of wild coffee. The results reveal very different strategies of wild coffee seedlings for coping with drought stress. The ecophysiological diversity shows the importance of Ethiopian wild coffee populations as gene pools for future breeding programs, and underlines the need for an in-situ conservation strategy. The study includes recommendations for coffee forest management and the use of wild arabica coffee in Ethiopia.

Solanum quitoense (Lulo) from the northern Andes is a fruit with an attractive taste. It has a high export potential but its production is hampered by insufficient pollination. Studies on the reproductive system of Lulo revealed that, due to their poricidal anthers, the flowers need pollinators for self- and cross-pollination. Pollination by native bumblebees significantly increases fruit set and quality. Experiments show that colonies of Bombus atratus can be reared in captivity and used in Lulo fields for providing increased pollination services. Modeling based on data on colony development reveal larva/workers ratio and the supply of pollen as main parameters for improving the rearing method.

Biofuel Crop Sustainability brings together the basic principles of agricultural sustainability and special stipulations for biofuels, from the economic and ecological opportunities and challenges of sustainable biofuel crop production to the unique characteristics of particular crops which make them ideal for biofuel applications. This book will be a valuable resource for researchers and professionals involved in biofuels development and production as well as agriculture industry personnel. Chapters focus the broad principles of resource management for ecological, environmental and societal welfare, the sustainability issues pertaining to several broad categories of biofuel crops , as well as the economics and profitability of biofuels on both a local and international scale. Coverage includes topics such as utilizing waste water for field crop irrigation and algae production, reliability of feedstock supply, marginal lands, and identifying crops with traits of significance for survival and growth on low fertility soils. The development of production practices with low external inputs of fertilizer, irrigation, and pesticides is also covered. Biofuel Crop Sustainability will be a valuable, up-to-date reference for all those involved in the rapidly expanding biofuels industry and sustainable agriculture research fields.

Soils of irrigated lands in the Aral Sea Basin are often plagued by high salinity,hampering profitable agriculture on these soils. In this context, the present study has three specific objectives: to identify techniques that enable a rapid estimation of soil salinity, to characterize its spatial distribution and to estimate its spatial distribution based on readily obtainable environmental parametersusing a Neural Network Model Approach. Topsoil salinity was highly variable atshort distances and terrain attributes were the most influential factors. The use of relationships between environmental attributes and soil salinity for upscaling spatial distribution of soil salinity from farm to district level proved to be satisfactory. A possible application is the development of salinity prediction toolsfor farm-level decision making.