Modeling Biome Distribution of Two Periods with Contrasting Climatic Conditions of the Holocene

Abstract

The climate of Europe underwent substantial changes throughout the Holocene (11.5–0 kyr BP). The climate during the mid-Holocene (6 kyr BP) was significantly warmer than the pre-industrial climate (0.1 kyr BP). Studying the biome distribution of these periods allows us to analyse the role of vegetation in the climate system response to these natural forcings and to better project vegetation behaviour in present-day warming. In this work, conducted within the framework of the TerraNova project, we present a modeling approach, which simulates climate and biome distribution of the two mentioned periods. The main objectives of this study are to investigate biome distribution of two periods with contrasting climatic conditions of the Holocene, and to analyse the impact of downscaling on prediction of biome distribution in Europe during the studied periods. The results of our study show spatial patterns of biome distribution of the two studied periods, and create a baseline for studying landscape transformations in combination with other factors, such as influence of human activities. The downscaling provides more detailed information on the spatial variability of biomes distribution, which is more suitable to study the local-scale processes compared to the coarse grid. This information is relevant for other partners of the TerraNova project who work at a local/regional scale. Our study contributes to better understanding of the vegetation-climate feedback of the past, which is important to investigate how the vegetation changes affect the local climate, and essential for studying human-environment interactions and developing strategies for sustainable solutions.

Presenters

Anhelina Zapolska
PhD candidate, Earth Sciences, VU Amsterdam, Noord-Holland, Netherlands

Frank Arthur
Universitetet i Sørøst-Norge

Details

Presentation Type

Poster Session

Theme

Ecological Realities

KEYWORDS

Biome Distribution, Vegetation Modeling, Climate Change, Mid-Holocene, Pre-Industrial

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