The role of ecosystem services in the spatial assessment of land degradation: a transdisciplinary study in the Ethiopian Great Rift Valley

Land degradation is a widespread problem that affects about 1.5 billion people globally. It can be defined as the decline in the productive capacity of the land, and the loss of functionality of ecosystems. Overall, land degradation leads to ecosystem services degradation, because it affects and causes the depletion of several soil functions (e.g. sediment retention, nutrient cycling, carbon stocks, and water retention). Therefore, it is also a constraint in securing food production and it could cause food insecurity. Hence, land degradation represents a considerable problem especially in developing countries, where people strongly rely on the ecosystems and natural resources for their livelihoods. The principal aim of this study was to assess land degradation by integrating different sources of knowledges and data, to derive a synthesis relevant to inform decision-making processes, and to target priority areas for conservation and restoration interventions. In this study, three ecosystem services (ESS) were modelled to infer land degradation in a small area, in the Halaba special woreda, located in the Ethiopian Great Rift Valley. In particular, sediment erosion and retention, nutrient retention and export, and carbon storage and sequestration were modelled. Data from a local soil survey, from global coverage datasets, and from a supervised land use cover classification were used for the ESS modelling. Remote Sensing data were used during the parametrisation phase of the ESS modelling. Local knowledges and perspectives were gathered using an extensive participatory approach that targeted the communities of three kebeles in the study area, and the experts of the Halaba woreda Agricultural Office. 33 focus group discussions and 32 semi-structured interviews were conducted in the summer 2016. The information acquired through the ESS modelling and during the participatory approach was then integrated in a Bayesian Belief Network (BBN), a probabilistic graphical model, to derive a spatial explicit land degradation risk assessment. The results showed that assessing land degradation through the lens of key ecosystem services represents a valid approach. The ESS modelling results showed that the study area is characterised by high soil erosion rates, low carbon storage and sequestration, and low nitrogen retention. Moreover, the ESS modelling also showed that using data from global coverage datasets could affect the reliability of the ESS assessment. Furthermore, the qualitative study, derived from the participatory approach, highlighted the presence of complex linkages between environmental and socio-economic factors, which exacerbate land degradation. The integration of ESS modelling results, participatory approach and literature data in the BBN proved to be an efficient approach to derive a synthesis of the several knowledges acquired during the several steps of this PhD project. Overall, this study demonstrated that a transdisciplinary and interdisciplinary approach is an effective means to address land degradation risks, taking into consideration people needs and priorities. In order to reverse land degradation trends, there is the need to adopt intense restoration and sustainable land management programs. However, there is also the need to couple conservation interventions with development strategies, such as market access and development, land tenure system improvements, off-farm job opportunities generation, and livelihoods diversification. This could foster land conservation and restoration, and could support sustainable economic growth and inclusive development.