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The multi-dimensional and dynamic nature of rangeland degradation makes accurate assessment a difficult challenge. Existing assessment methods rarely integrate different components of land degradation and local communities rarely participate, or derive results that can improve the sustainability of their land management. Sustainability indicators offer one solution to this problem. They can be used by a range of stakeholders to derive multi-disciplinary information that can be used to both monitor and respond to environmental change. However, it is increasingly claimed that existing sustainability indicators provide few benefits to local users who, as a consequence, rarely apply them. The thesis therefore starts by reviewing land degradation causes and theoretical models in semi-arid rangelands, and critically evaluates a range of degradation assessment methods in the semi-arid rangelands of Botswana. This shows that multi-source, multi-scale land degradation assessment can provide more accurate and reliable results than the use of any single technique alone. This information is used to identify potential land degradation “hotspots”, and a learning process for sustainability assessment is developed and tested in three of these problem areas. The process is designed to facilitate two-way and meaningful interaction between local communities, researchers and policy-makers to monitor environmental sustainability and respond appropriately. Application of the process identified a range of innovative management options that could prevent, reduce, reverse or help rangeland stakeholders adapt to land degradation. Communities identified a wide range of sustainability indicators, the majority of which were validated through field-based research. Local knowledge was more holistic than many published indicator lists for monitoring rangelands, encompassing vegetation, soil, livestock, wild animal and socio-economic indicators. By building on local knowledge, the indicators and management options were familiar to land users who could apply them without specialist training or equipment. Indicators and management options were integrated in a manual-style Decision Support System designed to help land managers easily monitor progress and adapt management to reach sustainability goals. These findings emphasise the value of local knowledge in rangeland monitoring and management.