4.7 Article

A new indicator approach to reconstruct agricultural land use in Europe from sedimentary pollen assemblages

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ELSEVIER
DOI: 10.1016/j.palaeo.2022.111051

Keywords

Cultural indicator pollen types; Human impact; Palynology; Palaeoecology; Archaeobotany; Archaeology; Europe

Funding

  1. Swiss National Science Foundation (SNSF) [169371]

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The reconstruction of human impact on vegetation and ecosystem change is crucial in palaeoecological studies. This study proposes a novel approach, the agricultural land use probability (LUP) index, to quantify human impact intensity on European ecosystems based on cultural indicator pollen types. The study demonstrates the potential of the LUP index for refining pollen-based land-use reconstructions and discusses the suitability of selected pollen types.
The reconstruction of human impact is pivotal in palaeoecological studies, as humans are among the most important drivers of Holocene vegetation and ecosystem change. Nevertheless, separating the anthropogenic footprint on vegetation dynamics from the impact of climate and other environmental factors (disturbances such as fire, erosion, floods, landslides, avalanches, volcanic eruptions) is a challenging and still largely open issue. For this purpose, palynologists mostly rely on cultural indicator pollen types and related indices that consist of sums or ratios of these pollen types. However, the high environmental and biogeographical specificity of cultural indicator plants hinders the application of the currently available indices to wide geographical settings. Furthermore, the achievable taxonomic resolution of cultural indicator pollen types may hamper their indicative capacity. In this study, we propose the agricultural land use probability (LUP) index, a novel approach to quantify human impact intensity on European ecosystems based on cultural indicator pollen types. From the 'classic' cultural indicators, we construct the LUP index by selecting those with the best indicator capacity based on bioindication criteria. We first train the LUP index using twenty palynological sequences along a broad environmental gradient, spanning from treeless alpine to subtropical mediterranean evergreen plant communities. We then validate the LUP index using independent pollen datasets and archaeological proxies. Finally, we discuss the suitability of the selected pollen types and the potential of the LUP index for quantifying Holocene human impact in Europe, concluding that careful application of the LUP index may significantly contribute to refining pollen-based land-use reconstructions.

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