Thresholds of potential concern as benchmarks in the management of African savannahs.
In the Kruger National Park (KNP), South Africa, ecosystem managers use a series of monitoring endpoints, known as thresholds of potential concern (TPCs), to define the upper and the lower levels of accepted variation in ecosystems. For woody vegetation, the current TPC suggests that woody cover should not drop by more than 80% of its 'highest ever' value. In this paper, we explore the utility of palaeoecological data in informing TPCs. We use calibrated fossil pollen data to explore variability in vegetation at two sites over the past 5000 years, to provide a long-term record of changes in woody vegetation cover and a context for interpreting more recent vegetation change. The fossil pollen data are calibrated using studies of modern pollen and vegetation from KNP; arboreal pollen percentage was simulated using pollen-landscape modelling software for savannah landscapes of varying woody vegetation cover, and the relationship between vegetation and pollen data was quantified using nonlinear regression. This quadratic equation was then applied to fossil pollen data in order to estimate woody vegetation cover from arboreal pollen percentages. Our results suggest that the TPCs have not been exceeded during the period represented in the pollen record, because estimated woody vegetation cover has remained above 20% of its highest ever value. By comparing the fossil pollen data with TPCs, our study demonstrates how palaeoecological data can be presented in a form that is directly relevant to management objectives.
Gillson
L
L
Environmental Change Institute, Oxford University Centre for the Environment, South Parks Road, Oxford OX1 3QY, UK. lindsey.gillson@uct.ac.za
Duffin
K I
KI
D002250:Carbon Radioisotopes / Q000032:analysis; D003247:Conservation of Natural Resources / Q000379:methods*; D004463:Ecology / Q000379:methods*; D017753:Ecosystem; D005580:Fossils; D049690:History, Ancient; D013058:Mass Spectrometry; D008962:Models, Theoretical; D011058:Pollen / Q000166:cytology; D011157:Population Dynamics; D012044:Regression Analysis; D012987:Soil / Q000032:analysis; D013019:South Africa; D014197:Trees / Q000254:growth & development*
D002250:Carbon Radioisotopes; D012987:Soil