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Spatial heterogeneity in ecosystem structure and productivity in a moist Kenyan savanna
Authors:D O Otieno  G O K’Otuto  B Jákli  P Schröttle  J N Maina  E Jung  J C Onyango
Institution:(1) Department of Plant Ecology, University of Bayreuth, 95440 Bayreuth, Germany;(2) University Botanic Garden, Maseno University, Maseno, 333, Kenya
Abstract:Topographic variations and disturbances are key sources of spatial heterogeneity in the ecosystem and may influence its functioning, productivity, and carbon (C) storage. In water controlled ecosystems, structural and functional heterogeneity become distinct during drought when the ecosystem processes are operating at their limits. We examined spatial heterogeneity arising from grazing, abandoned cropland, presence of Acacia trees, and termite mounds (termitaria). Soil water content (SWC) was significantly (P < 0.05) higher in termitaria and fenced (un-grazed) plots. Higher soil nitrogen (N) content occurred in the Acacia, termitaria, and fenced plots while total biomass was highest in the fenced plot. The termitaria plots showed the highest net ecosystem CO2 exchange (NEE), ecosystem respiration (R eco), and gross primary production (GPP) and were the only plots that were net CO2 sinks. Except in fenced plots, maximum GPP was positively correlated with SWC and green biomass in all the other plots. Green biomass and R eco were positively correlated with SWC. Shifting cultivation (abandoned farmlands) negatively affected soil quality, ecosystem CO2 assimilation, and productivity. Removal of grazing (cattle) from the ecosystem negatively influenced GPP, while the presence of termitaria and Acacia trees facilitated soil water and N availability and ecosystem productivity. We concluded that soil water availability was responsible for most of the localized differences in the savanna and has a strong influence on ecosystem C capture and storage. We recommend that future studies on savanna productivity and ecosystem CO2 fluxes should consider heterogeneity in the ecosystem in order to avoid bias and increase the accuracy of any estimates made.
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