Towards a virtual observatory for ecosystem services and poverty alleviation
For the indigenous communities of the Pacaya-Samira National Reserve in the Peruvian Amazon, turtle farming is a successful survival strategy. The practice keeps the natural animal population numbers up and provides a necessary source of food and income. However, the success of the activity is highly dependent on information about the erratic river level, which may flood nesting beaches at crucial times. In the Yasuni national park in the Ecuadorian Amazon, bush meat hunting regions are threatened by encroaching deforestation. At the same time, in the Andean headwaters of Ecuador, Peru and Bolivia, the availability and quality of irrigation water depends strongly on mountain wetland management, and is potentially threatened by global climate change.
These are striking examples of many situations where the livelihoods of local communities depend on crucial ecosystem services. However, sustainable management of these services is only possible using an advanced integration of climatic, hydrological, and ecological data.
Previous approaches to integrate such data had largely failed for a variety of reasons. In Pacaya Samira, little local data were available resulting in very large uncertainties in the model predictions. In the Andean highlands, local politicians and managers have difficulties interpreting model simulations and designing proper land management schemes. Finally, both systems can benefit strongly from the incorporation of local expert knowledge to reduce model uncertainties.
Recently, many methodologies for data integration and user interaction have been developed. They are known under the common umbrella of a "virtual observatory". The ultimate goal of a virtual observatory is a perfect integration of data, models and users. Worldwide, many coordinated activities are ongoing to make this integration a reality. However, far less attention has been paid to the question of how these developments can benefit environmental services management and poverty alleviation.
This project experimented with environmental prediction systems for the above mentioned case studies, using existing virtual observatory tools and developed, implemented and evaluated tools to improve the value of these systems in the specific conditions of poverty alleviation, i.e. improved communication of simulations, assessing the value of collected data, and integrating local managers' knowledge and practice in modelling systems.
Heavily relying on public domain software, open standards and existing virtual observatory efforts, the project developed a platform for interdisciplinary, cost-efficient and highly tailored environmental data analysis and simulation. This platform was available immediately for the selected case studies, thus enabling direct poverty alleviation action benefiting an estimated 15,000 local inhabitants.
Close collaboration with local stakeholders and integration in existing initiatives ensured quick adoption of the platform. For instance, the InfoAndina website of project partner CONDESAN which was integrated, had more than 1,600 registered users. At the same time, the project generated novel scientific insights in model simulation, communication and improvement in a developing context. The involvement of the Principal Investigator in the global virtual observatory community ensured that the research results benefit ongoing research in this area.
Dr Buytaert led further work on virtual observatories in mountainous areas in NE/K010239/1.