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Many semi arid savannas are prone to degradation, caused for example, by overgrazing or extreme climatic events, which often lead to shrub encroachment. Overgrazing by livestock affects vegetation and infiltration processes by directly altering plant composition (selective grazing) or by impacting soil physical properties (trampling). Water infiltration is controlled by several parameters, such as macropores (created by soil-burrowing animals or plant roots) and soil texture, but their effects have mostly been studied in isolation. Here we report on a study, in which we conducted infiltration experiments to analyze the interconnected effects of invertebrate-created macropores, shrubs and soil texture (sandy soil and loamy sand) on infiltration in two Namibian rangelands. Using structural equation modeling, we found a direct positive effect of shrub size on infiltration and indirectly via invertebrate macropores on both soil types. On loamy sands this effect was even stronger, but additionally, invertebrate-created macropores became relevant as a direct driver of infiltration. Our results provide new insights into the effects of vegetation and invertebrates on infiltration under different soil textures. Pastoralists should use management strategies that maintain a heterogeneous plant community that supports soil fauna to sustain healthy soil water dynamics, particularly on soils with higher loam content. Understanding the fundamental functioning of soil water dynamics in drylands is critical because these ecosystems are water-limited and support the livelihoods of many cultures worldwide.
Subterranean termites create tunnels (macropores) for foraging that can influence water infiltration and may lead to preferential flow to deeper soil layers. This is particularly important in water limited ecosystems such as semi-arid, agriculturally utilized savannas, which are particularly prone to land degradation and shrub-encroachment. Using termite activity has been suggested as a restoration measure, but their impact on hydrology is neither universal nor yet fully understood. Here, we used highly replicated, small-scale (50 x 50 cm) rain-simulation experiments to analyse the interacting effects of either vegetation (grass dominated vs. shrub dominated sites) or soil texture (sand vs. loamy sand) and termite foraging macropores on infiltration patterns. We used Brilliant Blue FCF as colour tracer to make the flow pathways in paired experiments visible, on either termite-disturbed soil or controls without surface macropores in two semi-arid Namibian savannas (with either heterogeneous soil texture or shrub cover). On highly shrub-encroached plots in the savanna site with heterogeneous soil texture, termite macropores increased maximum infiltration depth and total amount of infiltrated water on loamy sand, but not on sandy soil. In the sandy savanna with heterogeneous shrub cover, neither termite activity nor shrub density affected the infiltration. Termite's effect on infiltration depends on the soil's hydraulic conductivity and occurs mostly under ponded conditions, intercepting run-off. In semi-arid savanna soils with a considerable fraction of fine particles, termites are likely an important factor for soil water dynamics.
Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.