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Savannas are the only deciduous system where new leaf flush pre-empts the onset of suitable conditions for growth, a phenological phenomenon known as early-greening. Limited understanding of the frequency and drivers of the occurrence of early-greening in southern African savanna trees exists. We aimed to estimate the frequency of early-greening events across southern Africa and investigated potential environmental drivers of green-up. We selected and compared seven broad-leaved woodland sites where Burkea africana was a dominant species using remotely sensed data along a latitudinal gradient from South Africa to Zambia. Normalized difference vegetation index ( NDVI) values were extracted from the Moderate Resolution Imaging Spectroradiometer ( MODIS) satellite imagery at each site from January 2002 to June 2014. Using an austral year (July 1st-June 30th), early-greening was recorded if the green-up start date occurred prior to the onset date of seasonal rainfall. A latitudinal gradient of early-green-up was detected across southern Africa ( R2 = 0.74) with the two most northerly (Zambian) sites showing the earliest and most consistent green-up start dates (3 October ± 5.34 days). A strong latitudinal gradient was observed between the variability in the amount of rainfall in the first 6 months of green-up and the green-up start dates across southern Africa ( R2 = 0.92). Photoperiod appeared to play a role in areas where the onset of rainfall commenced late into the austral year. Mean maximum temperatures recorded 10 days prior to green-up start dates suggested a potential threshold of about 35°C, which could drive early-greening in the absence of rainfall. Correlations between the proportion of early-greening years and the above mentioned environmental factors indicated that rainfall variability had the strongest influence over the observed phenological gradient ( R2 = 0.96). Understanding early-greening in complex savanna systems is a vital step in furthering predictive phenological models under changing climatic conditions. [ABSTRACT FROM AUTHOR]

The need for accurate quantification of the amount of carbon stored in the environment has never been greater. Carbon sequestration has become a vital component of the battle against global climate change, and monitoring and quantifying this process are major challenges for policymakers. Plant allometric equations allow managers and scientists to quantify the biomass contained in a tree without cutting it down, and therefore can play a pivotal role in measuring carbon sequestration in forests and savannahs. These equations have been available since the beginning of the 20th century, but their usefulness depends on the ability to estimate the error associated with the equations - something which has received scant attention in the past. This paper provides a method based on the theory of linear regression and the lognormal distribution to derive confidence limits for estimates of biomass derived from plant allometric equations. Allometric equations for several southern African savannah species are provided, as well as the parameters and equations required to calculate the confidence intervals. This method was applied to data collected from a sampling campaign carried out in a savannah landscape at the Skukuza flux site, Kruger National Park, South Africa. Here the error was 10% of the total site biomass for the woody biomass and 2% for the leaf biomass. When the data were split into individual plots and used to estimate site biomass (as would occur in most sampling schemes) the error increased to 16% and 12% of the woody and leaf biomasses, respectively, as the sampling errors were added to the errors in the allometric equation. These methods can be used in any discipline that applies allometric equations, such as health sciences and animal physiology. [ABSTRACT FROM AUTHOR]

Theoretically, fire-tree cover feedbacks can maintain savanna and forest as alternative stable states. However, the global extent of fire-driven discontinuities in tree cover is unknown, especially accounting for seasonality and soils. We use tree cover, climate, fire, and soils data sets to show that tree cover is globally discontinuous. Climate influences tree cover globally but, at intermediate rainfall (1000 to 2500 millimeters) with mild seasonality (less than 7 months), tree cover is bimodal, and only fire differentiates between savanna and forest. These may be alternative states over large areas, including parts of Amazonia and the Congo. Changes in biome distributions, whether at the cost of savanna (due to fragmentation) or forest (due to climate), will be neither smooth nor easily reversible. [ABSTRACT FROM AUTHOR]