Transpiration dynamics support resource partitioning in African savanna trees and grasses

Citation: Holdo, R. M., & Nippert, J. B. (2015). Transpiration dynamics support resource partitioning in African savanna trees and grasses. Ecology, 96(6), 1466-1472. doi:10.1890/14-1986.1It is still far from clear whether and to what extent trees and grasses partition soil moisture in tropical savannas. A major reason for this is that we don't know how snapshot data on rooting differences translate into ecologically relevant patterns of water use at seasonal scales. We used stable isotopes in soil and stem water to quantify functional rooting profiles in grasses and two tree species in a South African savanna. Concurrently, we measured tree sap-flow velocity, grass canopy temperature (a transpiration correlate), and soil moisture content at multiple depths over the course of a growing season. We used lasso regression to identify the dominant soil moisture layers driving daily variation in tree and grass water-use metrics while controlling for weather variables. We found clear rooting depth differences between grasses (shallow) and trees (deep) from the isotopic data, and these patterns were strongly supported by the water-use data, which showed that grasses and trees predominantly responded to soil moisture availability at 5 and 40 cm depth, respectively. Our results provide a rare example of mechanistic support for the resource partitioning hypothesis in savannas, with important implications for our understanding of tree-grass dynamics under altered precipitation regimes

Predicted Impact of Barriers to Migration on the Serengeti Wildebeest Population

The Serengeti wildebeest migration is a rare and spectacular example of a once-common biological phenomenon. A proposed road project threatens to bisect the Serengeti ecosystem and its integrity. The precautionary principle dictates that we consider the possible consequences of a road completely disrupting the migration. We used an existing spatially-explicit simulation model of wildebeest movement and population dynamics to explore how placing a barrier to migration across the proposed route (thus creating two disjoint but mobile subpopulations) might affect the long-term size of the wildebeest population. Our simulation results suggest that a barrier to migration—even without causing habitat loss—could cause the wildebeest population to decline by about a third. The driver of this decline is the effect of habitat fragmentation (even without habitat loss) on the ability of wildebeest to effectively track temporal shifts in high-quality forage resources across the landscape. Given the important role of the wildebeest migration for a number of key ecological processes, these findings have potentially important ramifications for ecosystem biodiversity, structure, and function in the Serengeti

Disease and the Dynamics of Food Webs

What models and statistical tools can best help us assess how ecosystems respond to the impact of multiple factors, such as disease, predation, fire, and rain

A Disease-Mediated Trophic Cascade in the Serengeti and its Implications for Ecosystem C

The removal of rinderpest had cascading effects on herbivore populations, fire, tree density, and even ecosystem carbon in the Serengeti ecosystem of East Africa

Anthropogenic modifications to fire regimes in the wider Serengeti‐Mara ecosystem

Fire is a key driver in savannah systems and widely used as a land management tool. Intensifying human land uses are leading to rapid changes in the fire regimes, with consequences for ecosystem functioning and composition. We undertake a novel analysis describing spatial patterns in the fire regime of the Serengeti‐Mara ecosystem, document multidecadal temporal changes and investigate the factors underlying these patterns. We used MODIS active fire and burned area products from 2001 to 2014 to identify individual fires; summarizing four characteristics for each detected fire: size, ignition date, time since last fire and radiative power. Using satellite imagery, we estimated the rate of change in the density of livestock bomas as a proxy for livestock density. We used these metrics to model drivers of variation in the four fire characteristics, as well as total number of fires and total area burned. Fires in the Serengeti‐Mara show high spatial variability—with number of fires and ignition date mirroring mean annual precipitation. The short‐term effect of rainfall decreases fire size and intensity but cumulative rainfall over several years leads to increased standing grass biomass and fuel loads, and, therefore, in larger and hotter fires. Our study reveals dramatic changes over time, with a reduction in total number of fires and total area burned, to the point where some areas now experience virtually no fire. We suggest that increasing livestock numbers are driving this decline, presumably by inhibiting fire spread. These temporal patterns are part of a global decline in total area burned, especially in savannahs, and we caution that ecosystem functioning may have been compromised. Land managers and policy formulators need to factor in rapid fire regime modifications to achieve management objectives and maintain the ecological function of savannah ecosystems

Spatial patterning of soil microbial communities created by fungus‐farming termites

Spatially overdispersed mounds of fungus‐farming termites (Macrotermitinae) are hotspots of nutrient availability and primary productivity in tropical savannas, creating spatial heterogeneity in communities and ecosystem functions. These termites influence the local availability of nutrients in part by redistributing nutrients across the landscape, but the links between termite ecosystem engineering and the soil microbes that are the metabolic agents of nutrient cycling are little understood. We used DNA metabarcoding of soils from Odontotermes montanus mounds to examine the influence of termites on soil microbial communities in a semi‐arid Kenyan savanna. We found that bacterial and fungal communities were compositionally distinct in termite‐mound topsoils relative to the surrounding savanna, and that bacterial communities were more diverse on mounds. The higher microbial alpha and beta diversity associated with mounds created striking spatial patterning in microbial community composition, and boosted landscape‐scale microbial richness and diversity. Selected enzyme assays revealed consistent differences in potential enzymatic activity, suggesting links between termite‐induced heterogeneity in microbial community composition and the spatial distribution of ecosystem functions. We conducted a large‐scale field experiment in which we attempted to simulate termites’ effects on microbes by fertilizing mound‐sized patches; this altered both bacterial and fungal communities, but in a different way than natural mounds. Elevated levels of inorganic nitrogen, phosphorus and potassium may help to explain the distinctive fungal communities in termite‐mound soils, but cannot account for the distinctive bacterial communities associated with mounds

Comment on "The extent of forest in dryland biomes"

Bastin et al (Reports, 12 May 2017, p. 635) infer forest as more globally extensive than previously estimated using tree cover data. However, their forest definition does not reflect ecosystem function or biotic composition. These structural and climatic definitions inflate forest estimates across the tropics and undermine conservation goals, leading to inappropriate management policies and practices in tropical grassy ecosystems

Anthropogenic modifications to fire regimes in the wider Serengeti-Mara ecosystem

Fire is a key driver in savannah systems and widely used as a land management tool. Intensifying human land uses are leading to rapid changes in the fire regimes, with consequences for ecosystem functioning and composition. We undertake a novel analysis describing spatial patterns in the fire regime of the Serengeti‐Mara ecosystem, document multidecadal temporal changes and investigate the factors underlying these patterns. We used MODIS active fire and burned area products from 2001 to 2014 to identify individual fires; summarizing four characteristics for each detected fire: size, ignition date, time since last fire and radiative power. Using satellite imagery, we estimated the rate of change in the density of livestock bomas as a proxy for livestock density. We used these metrics to model drivers of variation in the four fire characteristics, as well as total number of fires and total area burned. Fires in the Serengeti‐Mara show high spatial variability—with number of fires and ignition date mirroring mean annual precipitation. The short‐term effect of rainfall decreases fire size and intensity but cumulative rainfall over several years leads to increased standing grass biomass and fuel loads, and, therefore, in larger and hotter fires. Our study reveals dramatic changes over time, with a reduction in total number of fires and total area burned, to the point where some areas now experience virtually no fire. We suggest that increasing livestock numbers are driving this decline, presumably by inhibiting fire spread. These temporal patterns are part of a global decline in total area burned, especially in savannahs, and we caution that ecosystem functioning may have been compromised. Land managers and policy formulators need to factor in rapid fire regime modifications to achieve management objectives and maintain the ecological function of savannah ecosystems.Natural Environment Research Council, Grant/Award Number: JZG10015; Leverhulme Trust, Grant/Award Number: IN‐2014‐022; Vetenskapsrådet; Sida and Formas, Grant/Award Number: 2016‐06355.http://wileyonlinelibrary.com/journal/gcbhj2019Zoology and Entomolog

Home on the Range: Factors Explaining Partial Migration of African Buffalo in a Tropical Environment

Partial migration (when only some individuals in a population undertake seasonal migrations) is common in many species and geographical contexts. Despite the development of modern statistical methods for analyzing partial migration, there have been no studies on what influences partial migration in tropical environments. We present research on factors affecting partial migration in African buffalo (Syncerus caffer) in northeastern Namibia. Our dataset is derived from 32 satellite tracking collars, spans 4 years and contains over 35,000 locations. We used remotely sensed data to quantify various factors that buffalo experience in the dry season when making decisions on whether and how far to migrate, including potential man-made and natural barriers, as well as spatial and temporal heterogeneity in environmental conditions. Using an information-theoretic, non-linear regression approach, our analyses showed that buffalo in this area can be divided into 4 migratory classes: migrants, non-migrants, dispersers, and a new class that we call “expanders”. Multimodel inference from least-squares regressions of wet season movements showed that environmental conditions (rainfall, fires, woodland cover, vegetation biomass), distance to the nearest barrier (river, fence, cultivated area) and social factors (age, size of herd at capture) were all important in explaining variation in migratory behaviour. The relative contributions of these variables to partial migration have not previously been assessed for ungulates in the tropics. Understanding the factors driving migratory decisions of wildlife will lead to better-informed conservation and land-use decisions in this area