Spatial heterogeneity in ecosystem structure and productivity in a moist Kenyan savanna

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 CO 2 exchange (NEE), ecosystem respiration (R eco ), and gross primary production (GPP) and were the only plots that were net CO 2 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 CO 2 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 CO 2 fluxes should consider heterogeneity in the ecosystem in order to avoid bias and increase the accuracy of any estimates made.

Interactive influence of rainfall manipulation and livestock grazing on species diversity of the herbaceous layer community in a humid savannah in Kenya

“…The composition of herbaceous vegetation varied considerably within our study sites irrespective of rainfall treatment, which characterises the heterogeneity of Lambwe valley (Allsopp and Baldry, 1972). Spatial variation in the composition of herbaceous species may be attributed to the ability of individual species to adapt to local and edaphic conditions (Silva et al., 2013, Augustine, 2003), which are different within our sites (Otieno et al., 2011). It is possible that the lower vegetation dominance in the grazed plots (Fig.…”

Differential Effects of Fire on Small Mammal Communities in the Busanga Flood Plain, Zambia

“…This is even more so as a review of the small mammal inventories in KNP based on published reports had indicated higher species richness for woodlands (Namukonde et al, in press). Miombo is considered a vegetation formation growing on poor soil and thus not being very productive (East, 1984;Desanker, Frost, Justice, & Scholes, 1997;Campbell et al, 2007), while termitaria are characterized by good soil conditions that promotes plant growth (Otieno et al, 2011). While high productivity soil results in high biomass across trophic levels, the link between productivity and species diversity remains unclear despite decades of research and seems to depend on local conditions, including habitat structure that is likely to obscure productivity-diversity relationships when considered across different vegetation types (Liang et al, 2016, Simons et al, 2017Socher et al, 2012Socher et al, , 2013Srivastava & Lawton 1998).…”

“…NMDS integrates community measures, that is, dissimilarity, diversity, and abundance to generate matrices. Differences in species composition between vegetation types and fire effects were determined by permutational multivariate analyses of variance (perMANOVA) used in the function adonis() in R package vegan (Oksanen et al, 2015). The analyses were based on community dissimilarity matrices by calculating Bray-Curtis dissimilarities of relative abundance data (Nopper, Ranaivojaona, Riemann, Ro¨del, & Ganzhorn, 2017).…”

Anaplasma and Theileria Pathogens in Cattle of Lambwe Valley, Kenya: A Case for Pro-Active Surveillance in the Wildlife–Livestock Interface

“…Rainfall is bimodal, peaking in April–June and September–November. The annual dry and hot period is from January to March [ 21 ]. The community in Lambwe Valley practice subsistence farming, fishing, and animal husbandry.…”