Second, drawing on these maps, we will calculate connectivity indices through time for individual woody vegetation patches as well as for the entire landscape. This, in turn, will generate measures of landscape context for each site, as well as predictions of (a) particularly well-connected and therefore species-rich sites, versus (b) poorly connected sites which should be relatively species-poor. Third, we will test these predictions using the empirical data from sub-project 1 of our research unit. Fourth, we will return to the tree cover data in order to calculate spatially-explicit remote-sensing based indices of ecosystem functioning for the entire study area, and to quantify differences in functioning between restored and non-restored sites. Given the global proliferation of large-scale restoration initiatives, it is important to better understand how ambitious tree planting influences landscape context, connectivity, biodiversity patterns and ecological functioning at a landscape scale. Because of Rwanda’s ambitious restoration efforts, the country provides an exciting opportunity to advance knowledge about how ongoing changes in land cover and connectivity shape ecosystems. This sub-project thus makes contributions to the fields of landscape ecology and restoration ecology. In addition, this sub-project will benefit the research unit as a whole by generating an important spatiotemporal understanding that is useful for all other sub-projects.
• Different time periods correspond to distinct types and patterns of tree cover loss and/or restoration.
• Time series of tree cover can be used to identify sites with high immigration credit.
• Current “bright spots” in vegetation structure and diversity coincide with connected restoration sites.
• Restored sections of the landscape have higher ecosystem functioning relative to unrestored, but otherwise similar sections of the landscape.