The Watershed Exploration Tool allows watersheds to be compared for their biodiversity and ecosystem function importance, for current (2005) and future (2050) scenarios in three tropical regions: the Great Lakes region of Africa, the Mekong Basin in South-East Asia and the Andes in South America.
Land conversion and intensification of agricultural systems seem unavoidable and likely to result in loss of biodiversity and ecosystem functions. The MacArthur Foundation funded research by UN Environment WCMC to address the urgent need to understand trade-offs between land uses, and to provide such information and analyses to stakeholders and decision makers. This study combines future scenarios with land use modelling, to evaluate priorities for conservation or other actions, in order to balance demands on land for regions characterised by high biodiversity and poverty.
The project aims to: i) provide a baseline to assess future impacts of development and ii) identify current and potential future priorities to inform activities of stakeholders, in relation to impacts of major commodity markets on biodiversity and ecosystem functions.
For full details of the project see here
A second study funded by the MacArthur foundation provided more detailed analysis for the Lake Victoria basin, based on smaller watersheds and land use modelling from all five countries surrounding the lake. Results can be explored via the Lake Victoria Basin tab on the home page.
- Analysis was carried out using i) global and ii) regionally developed scenarios of change.
- These scenarios were used as a basis for land use modelling using LandSHIFT to produce land cover outputs for current and future time periods.
- The LandSHIFT model considers drivers of land use change such as population change, trends in commodity markets and agricultural production, in addition to land cover data from GLC-2000. Watershed importance values were derived from linking the land cover outputs from land use modelling, to biodiversity and ecosystem functions.
- Biodiversity importance was based on IUCN species ranges for amphibians, mammals and birds in combination with their habitat affiliations and modelled land cover.
- Ecosystem function importance was based on a landscape functions approach and modelled land cover.
The results for the watersheds in this tool are not comparable between the three regions or between global and regional scenarios. Results represent mean values for watersheds and thus may not reflect realities at local scales.
For more information download the final spatial analysis report here, journal articles by van Soesbergen et al, (2016) and Mason-D’Cruz, D (2016), or see links below:
- Bartholome, E., Belward, A. (2005) GLC2000: a new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing, 26, 1959-1977.
- Kienast, F., Bolliger, J., Potschin, M., De Groot, R.S., Verburg, P.H., Heller, I., Wascher, D., Haines-Young, R. Assessing landscape functions with broad scale environmental data: insights from a prototype development for Europe (2009) Environmental management 44, 1099-1120.
- IUCN (2014) IUCN Red List of threatened species. Gland: IUCN. Available at http://www.iucnredlist.org (accessed 2014).
- Mason-D’Cruz, D., Vervoort, J. M., Palazzo, A., Islam, S., Lord, S., Helfgott, A., Havlík, P., Peou, R., Sassen, M., Veeger, M., van Soesbergen, A., Arnell, A. P., Stuch, B., Arslan, A., Lipper, L. (2016). Multi-factor, multi-state, multi-model scenarios: exploring food and climate futures for Southeast Asia. Environmental Modelling & Software, 83, 255–270.
- Schaldach, R., Alcamo, J., Koch, J., Kolking, C., Lapola, D.M., Schungel, J., Priess, J.A. An integrated approach to modelling land-use change on continental and global scales (2011). Environmental modelling and software 26, 1041-1051.
- van Soesbergen, A., Arnell, A. P., Sassen, M., Stuch, B., Schaldach, R., Göpel, J., … Palazzo, A. (2016). Exploring future agricultural development and biodiversity in Uganda, Rwanda and Burundi: a spatially explicit scenario-based assessment. Regional Environmental Change, 1–12.