›› 2014, Vol. 24 ›› Issue (1): 76-92.doi: 10.1007/s11442-014-1074-6

• Research Articles • Previous Articles     Next Articles

Human-driven topographic effects on the distribution of forest in a flat, lowland agricultural region

Mette V. ODGAARD1,2, Peder K. BøCHER2, Tommy DALGAARD1, Jesper E. MOESLUND1,2,3, Jens-Christian SVENNING   

  1. 1. Department of Agroecology, Aarhus University, Blichers Allè|20, DK-8830 Tjele, Denmark;
    2. Ecoinformatics &|Biodiversity Group, Department of Bioscience, Aarhus University, Ny Munkegade 114, DK-8000 Aarhus C, Denmark;
    3. Department of Computer Science, Aarhus University, Åbogade 34, DK-8200 Aarhus N, Denmark
  • Received:2012-08-29 Revised:2013-09-10 Online:2014-02-15 Published:2014-02-15
  • About author:Mette Vestergaard Odgaard, PhD Candidate, specialized in landscape dynamics and geographic information science. E-mail:mettev.odgaard@agrsci.dk


Complex topography buffers forests against deforestation in mountainous regions. However, it is unknown if terrain also shapes forest distribution in lowlands where human impacts are likely to be less constrained by terrain. In such regions, if important at all, topographic effects will depend on cultural-historical factors and thus be human-driven (anthropogenic) rather than natural, except in regions where the general climate or extreme soils limit the occurrence of forests. We used spatial regression modeling to assess the extent to which topographic factors explain forest distribution (presence-absence at a 48×48 m resolution) in a lowland agricultural region (Denmark, 43,075 km2) at regional and landscape scales (whole study area and 10×10 km grid cells, respectively), how landscape-scale forest-topography relationships vary geographically, and which potential drivers (topographic heterogeneity, forest cover, clay content, coastal/inland location) determine this geographic heterogeneity. Given a moist temperate climate and non-extreme soils all landscapes in Denmark would naturally be largely forest covered, and any topographic relationships will be totally or primarily human-driven. At regional scale, topographic predictors explained only 5% of the distribution of forest. In contrast, the explanatory power of topography varied from 0%-61% at landscape scale, with clear geographic patterning. Explanatory power of topography at landscape scale was moderately dependent on the potential drivers, with topographic control being strongest in areas with high topographic heterogeneity and little forest cover. However, these conditioning effects were themselves geographically variable. Our findings show that topography by shaping human land-use can affect forest distribution even in flat, lowland regions, but especially via localized, geographically variable effects.

Key words: Europe, forest cover, geographically weighted regression, human impact, landscape development, topography, vegetation distribution