Esther Githumbi

Researcher

Research areas and keywords

UKÄ subject classification

  • Climate Research

Keywords

  • pollen analysis, land use change, Palaeoecology, fire ecology

Research

My research has a clear MERGE (a Strategic Research Area of the Swedish government) focus. Especially on Late Quaternary land cover change primarily in East Africa through the use of palaeocological proxies such as pollen and also in Europe using REVEALS reconstructions.

Research

REAL

The REAL project had an aim to provide long-term historical perspective on human-environment interactions to enable sustainable use of resources. I was involved in the development of new long-term records of change as well as integration of available records of past environmental change (from different sites a diverse range of indicators) to accurately document past ecosystem dynamics in East Africa. One of my sites was located in the Mau Forest which is the largest remaining block of closed canopy forest in East Africa providing a ~16000 year record of forest change. My other sites were located in the Amboseli savannah providing multiple records of change within the savannah since ~5000 cal yr BP. This sites were integrated and discussed within the larger East African spatial context to provide a description of vegetation change, fire history, climate and land use where there was collaborating evidence from other records. The outcomes from the different projects involved are available here REAL.

LandClimII

LandClimII (Land and Climate Interactions in Europe during the Holocene) aims to quantify the biogeophysical and biogeochemical forcings from anthropogenic deforestation on regional Holocene climate in Europe; I am involved in the pollen-based reconstruction of land cover. The project builds on Swedish research-front developments in several areas; regional climate modelling for land-atmosphere coupling studies (LU, SMHI), new generation global Earth system modelling (LU, SMHI, SU), pollen-based reconstruction of plant abundance/land cover (LnU), iv) dynamic vegetation modelling (LU), and v) spatial statistical Bayesian modelling to combine gridded and point data for land cover mapping (LU, LnU). State-of-the-art descriptions of past land cover (natural and human-induced/deforested) at a high spatial resolution will be achieved using a dynamic, process-based vegetation model, scenarios of past anthropogenic deforestation, pollen-based quantitative reconstructions of past vegetation, and statistical modelling. The climate runs will be performed for 2.5k and 1k with natural or anthropogenic land cover in order to identify the possible biogeophysical forcing of deforestation.