Asymmetric response of forest and grassy biomes to climate variability across the African Humid Period : influenced by anthropogenic disturbance?

A comprehensive understanding of the relationship between land cover, climate change and disturbance dynamics is needed to inform scenarios of vegetation change on the African continent. Although significant advances have been made, large uncertainties exist in projections of future biodiversity and ecosystem change for the world's largest tropical landmass. To better illustrate the effects of climate–disturbance–ecosystem interactions on continental‐scale vegetation change, we apply a novel statistical multivariate envelope approach to subfossil pollen data and climate model outputs (TraCE‐21ka). We target paleoenvironmental records across continental Africa, from the African Humid Period (AHP: ca 14 700–5500 yr BP) – an interval of spatially and temporally variable hydroclimatic conditions – until recent times, to improve our understanding of overarching vegetation trends and to compare changes between forest and grassy biomes (savanna and grassland). Our results suggest that although climate variability was the dominant driver of change, forest and grassy biomes responded asymmetrically: 1) the climatic envelope of grassy biomes expanded, or persisted in increasingly diverse climatic conditions, during the second half of the AHP whilst that of forest did not; 2) forest retreat occurred much more slowly during the mid to late Holocene compared to the early AHP forest expansion; and 3) as forest and grassy biomes diverged during the second half of the AHP, their ecological relationship (envelope overlap) fundamentally changed. Based on these asymmetries and associated changes in human land use, we propose and discuss three hypotheses about the influence of anthropogenic disturbance on continental‐scale vegetation change

A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity.

Quantitative structure-activity relationships (QSARs) for ecotoxicity can be used to fill data gaps and limit toxicity testing on animals. QSAR development may additionally reveal mechanistic information based on observed patterns in the data. However, the use of descriptive summary statistics for toxicity, such as the 4-day LC50 for fish, introduces bias and ignores valuable kinetic information in the data. Biology-based methods use all of the toxicity data in time to derive time-independent and unbiased parameter estimates. Such an approach offers whole new opportunities for mechanism-based QSAR development. In this paper, we apply the hazard model from DEBtox to analyse survival data for fathead minnows (Pimephales promelas). Different modes of action resulted in different patterns in the parameter estimates, and therefore, the toxicity data by themselves reveal insight into the actual mechanism of toxic action

Geochemical identity of pre-Dogon and Dogon populations at Bandiagara (Mali, 11th–20th cent. AD)

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