Fire and climate change impacts on lowland forest composition in northern Congo during the last 2580 years from palaeoecological analyses of a seasonally flooded swamp
Fire and climate change impacts on lowland forest composition in northern Congo during the last 2580 years from palaeoecological analyses of a seasonally flooded swamp
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DOI:
10.1177/0959683608098954
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发表时间:
2009-02-01
期刊:
影响因子:
2.4
通讯作者:
Bailey, Richard M.
中科院分区:
文献类型:
--
作者:
Brncic, Terry M.;Willis, Kathy J.;Bailey, Richard M.
The mixed semi-evergreen forests in lowland central equatorial Africa can contain many elements of secondary vegetation. This raises the question of what factors have determined the current forest composition in this region. Is this forest in the process of succession after natural climatic variation and/or anthropogenic disturbances in the past, or is it a stable forest type? This paper presents a multiproxy palaeoecological analysis of a sedimentary sequence taken from a small sedimentary basin located in logged semi-evergreen lowland forest in northern Congo-Brazzaville which addresses these questions. Analyses undertaken included fossil pollen, geochemical and microscopic charcoal. Geochemical results were interpreted as a proxy for rainfall, and showed that northem Congo has experienced changes in rainfall during the past 2580 years, while microscopic charcoal concentrations indicated increased burring from approximately 1240 cal. yr BP to the present. Analysis of the fossil pollen assemblages showed that although light-demanding taxa were a major constituent of this forest throughout the sequence, shade-tolerant taxa were more abundant in the forest prior to 1345 cal. yr BP. Increases in aridity and/or droughts after 1345 cal. yr BP, and an increase in fire after 1240 cal. yr BP resulted in a semi-evergreen forest with abundant pioneers that persisted with minor changes in composition during the last 900 years, even during a period of increased rainfall from 400 to 100 cal. yr BP. These data may guide conservation policy by predicting potential consequences of future climate change and the impact of logging.