Constraining the Deforestation History of Europe: Evaluation of Historical Land Use Scenarios with Pollen-Based Land Cover Reconstructions

Abstract

Anthropogenic land cover change (ALCC) is the most important transformation of the Earth system that occurred in the preindustrial Holocene, with implications for carbon, water and sediment cycles, biodiversity and the provision of ecosystem services and regional and global climate. For example, anthropogenic deforestation in preindustrial Eurasia may have led to feedbacks to the climate system: both biogeophysical, regionally amplifying winter cold and summer warm temperatures, and biogeochemical, stabilizing atmospheric CO 2 concentrations and thus influencing global climate. Quantification of these effects is difficult, however, because scenarios of anthropogenic land cover change over the Holocene vary widely, with increasing disagreement back in time. Because land cover change had such widespread ramifications for the Earth system, it is essential to assess current ALCC scenarios in light of observations and provide guidance on which models are most realistic. Here, we perform a systematic evaluation of two widely-used ALCC scenarios (KK10 and HYDE3.1) in northern and part of central Europe using an independent, pollen-based reconstruction of Holocene land cover (REVEALS). Considering that ALCC in Europe primarily resulted in deforestation, we compare modeled land use with the cover of non-forest vegetation inferred from the pollen data. Though neither land cover change scenario matches the pollen-based reconstructions precisely, KK10 correlates well with REVEALS at the country scale, while HYDE systematically underestimates land use with increasing magnitude with time in the past. Discrepancies between modeled and reconstructed land use are caused by a number of factors, including assumptions of per-capita land use and socio-cultural factors that cannot be predicted on the basis of the characteristics of the physical environment, including dietary preferences, long-distance trade, the location of urban areas and social organization.

Recent Deforestation Pattern Changes (2000–2017) in the Central Carpathians: A Gray-Level Co-Occurrence Matrix and Fractal Analysis Approach

“…Deforestation causes significant perturbations in the integrity of forest ecosystems. The fragmentation of forests due to deforestation causes flash floods [11,12], landslides [13][14][15], soil degradation [5,16], loss of biodiversity [17,18] and increases in CO 2 emissions [19][20][21]. Deforestation may be the result of logging and harvesting practices or can be a permanent conversion to other land uses (i.e., fires, agriculture, and development of human settlements) [22].…”

Finding the magnitude of human-induced Northern Hemisphere land-cover transformation between 6 and 0.2 ka BP

“…For example, Roberts et al (2018) show that REVEALS-based past European land-cover reconstructions differ significantly from those of other pollen-based methods for large parts of the Holocene (Woodbridge et al, this issue). Kaplan et al (2017) demonstrate that the KK scenarios of European Holocene deforestation are closer to REVEALS estimates of open-land cover than the HYDE scenarios version 3.1.…”

“…For example, Roberts et al (2018) show that REVEALS-based past European land-cover reconstructions differ significantly from those of other pollen-based methods for large parts of the Holocene (Woodbridge et al, this issue). Kaplan et al (2017) demonstrate that the KK scenarios of European Holocene deforestation are closer to REVEALS estimates of open-land cover than the HYDE scenarios version 3.1.REVEALS requires several input variables that are not typically needed for other types of paleovegetation reconstructions, including lake or bog size, RPPs, and fall speed of pollen; this information may be missing in legacy data. LandCover6k has led an international effort to gather the relevant knowledge and data for this new generation of landcover reconstructions.…”

River Systems and the Anthropocene: A Late Pleistocene and Holocene Timeline for Human Influence

“…The HYDE 3.2 model uses historical population data and land-use allocation algorithms [8,9]. Model results have high uncertainty levels, especially for the earlier Holocene, because the quality of historical population data varies in time and space and because the models depend on assumptions about the relationship between population and land use and sociocultural factors [241]. Land-use data are reasonably reliable for rice-based civilisations of Asia and hydraulic civilisations of North Africa and the Mediterranean, but the area of grazing land is poorly constrained.…”