The dissertation deals with the factors both physical and human that impact biomass levels in the case of seasonally dry tropical forests (SDTF) and discusses how the findings might help to improve REDD+ policy in Mexico. The central part of the dissertation is made up of three published articles. First the study explores the extent to which aboveground biomass levels in the SDTF could be predicted using linear and non-linear relationships at regional (that is to say, multi-community) scale with physical variables such as altitude, slope and insolation. Second, more complex modeling approaches are used to related aboveground biomass levels to local topographic variables, which are systematically replicated in the landscape, such as convexity/concavity of the terrain, in order to spatially predict standing biomass of SDTF within rural communities. Third, the dissertation addresses the intensification of current shifting agricultural practices in the study area and evaluates the impact of shifting cultivation on carbon stocks. This section considers how cultivation cycles can be optimized to promote reduction in carbon emission. Finally, the results of the three empirical chapters are discussed, to evaluate how the results of the thesis could be used to support carbon enhancement projects by communities in Mexico.
|Award date||21 Jun 2018|
|Place of Publication||Enschede|
|Publication status||Published - 21 Jun 2018|