Skip to main content
Log in

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

  • Published:
Journal of Geographical Sciences Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Acácio V, Holmgren M, Moreira F et al., 2010. Oak persistence in Mediterranean landscapes: The combined role of management, topography, and wildfires. Ecology and Society, 15: 1–17.

    Google Scholar 

  • Akaike H, 1973. Information theory and an extension of the maximum likelihood principle. In: Petrov B N, Csáki F (eds). 2nd International Symposium on Information Theory. Budapest, p.267.

    Google Scholar 

  • Bellemare J, Motzkin G, Foster D R, 2002. Legacies of the agricultural past in the forested present: An assessment of historical land-use effects on rich mesic forests. Journal of Biogeography, 29: 1401–1420.

    Article  Google Scholar 

  • Bonan G B, 2008. Forests and climate change: Forcings, feedbacks, and the climate benefits of forests. Science, 320: 1444–1449.

    Article  Google Scholar 

  • Brunsdon C, McClatchey J, Unwin D J, 2001. Spatial variations in the average rainfall-altitude relationship in Great Britain: An approach using geographically weighted regression. International Journal of Climatology, 21: 455–466.

    Article  Google Scholar 

  • Burnham K P, Anderson D R, 2002. Information and likelihood theory: A basis for model selection and inference. In: Burnham K P, Anderson D R (eds). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. New York, p.49.

    Google Scholar 

  • Cruz Ruggiero P G, Batalha M A, Pivello V R et al., 2002. Soil-vegetation relationships in cerrado (Brazilian savanna) and semideciduous forest, Southeastern Brazil. Plant Ecology, 160: 1–16.

    Article  Google Scholar 

  • Dalgaard T, Guul-Simonsen F, Liboriussen T, 2008. Landbruget i romantikken. In: Høiris O, Ledet T (eds). Romantikkens verden. Natur, menneske, samfund, kunst og kultur. Aahus, Denmark, p.87.

    Google Scholar 

  • Danish Ministry of the Environment, National Survey and Cadastre, 2010. (http://www.kms.dk/Emner/Landkor-(http://www.kms.dk/Emner/Landkortogtopografi/TopografiskeDatabaser/).

  • Dessie G, Christiansson C, 2008. Forest decline and its causes in the south-central rift valley of Ethiopia: Human impact over a one hundred year perspective. AMBIO: A Journal of the Human Environment, 37: 263–271. ESRI, 2010. ArcGIS ver. 10. USA.

    Article  Google Scholar 

  • Ewel J, 1999. Natural systems as models for the design of sustainable systems of land use. Agroforestry Systems, 45: 1–21.

    Article  Google Scholar 

  • Faraway J J, 2006. Binomial data. In: Carlin B P, Chatfield C, Tanner M et al. (eds). Extending the Linear Model with R. Generalized Linear, Mixed Effects and Nonparametric Regression Models. New York, p.25.

    Google Scholar 

  • Flinn K M, Vellend M, Marks P L, 2005. Environmental causes and consequences of forest clearance and agricultural abandonment in central New York, USA. Journal of Biogeography, 32: 439–452.

    Article  Google Scholar 

  • Fotheringham A S, Brunsdon C, Charlton M, 2001. Scale issues and geographically weighted regression. In: Nicholas J Tate, Peter M Atkinson (eds). Modelling Scale in Geographical Information Science. New York, USA, p.123.

    Google Scholar 

  • Fritzbøger B, 1994. Da landet blev skov. In: Kulturskoven. Bo Fritzbøger(ed). Nordisk Forlag A S. Copenhagen, p.24.

    Google Scholar 

  • Fritzbøger B, Odgaard B, 2010. Skovenes historie. In: Møller P F (ed.). Naturen i Danmark, skovene (The nature in Denmark, the forest). Denmark, p.55.

    Google Scholar 

  • Gellrich M, Zimmermann N E, 2007. Investigating the regional-scale pattern of agricultural land abandonment in the Swiss mountains: A spatial statistical modelling approach. Landscape and Urban Planning, 79: 65–76.

    Article  Google Scholar 

  • Greve M H, Greve M B, Bøcher P B et al., 2007. Generating a Danish raster-based topsoil property map combining choropleth maps and point information. Danish Journal of Geography, 107: 1–12.

    Article  Google Scholar 

  • Greve M, Lykke A M, Blach-Overgaard A et al., 2011. Environmental and anthropogenic determinants of vegetation distribution across Africa. Global Ecology and Biogeography, 20: 661–674.

    Article  Google Scholar 

  • Hemmavanh C, Ye Y, Yoshida A, 2010. Forest land use change at Trans-Boundary Laos-China Biodiversity Conservation Area. Journal of Geographical Sciences, 20(6): 889–898.

    Article  Google Scholar 

  • Hernández H R, Robledo M A, Rivera J R A et al., 2008. Spatial configuration of land-use/land-cover in the Pujal-Coy project area, Huasteca Potosina region, Mexico. AMBIO: A Journal of the Human Environment, 37: 381–389.

    Article  Google Scholar 

  • Hofera G, Bunceb R G H, Edwardsc P J et al., 2011. Use of topographic variability for assessing plant diversity in agricultural landscapes. Agriculture, Ecosystems and Environment, 142: 144–148.

    Article  Google Scholar 

  • Holm P, 2000. Kysternes erhverv og bebyggelse. In: Møller P G, Holm P, Rasmussen L (eds). Aktører i landskabet. Odense University Studies in History and Social Science vol. 232. Denmark, p.179.

    Google Scholar 

  • Hottola J, Siitonen J, 2008. Significance of woodland key habitats for polypore diversity and red-listed species in boreal forests. Biodiversity Conservation, 17: 2559–2577.

    Article  Google Scholar 

  • Katz D S W, Lovett G M, Canham C D et al., 2010. Legacies of land use history diminish over 22 years in a forest in southeastern New York. The Journal of the Torrey Botanical Society, 137: 236–251.

    Article  Google Scholar 

  • Kreft H, Jetz W, 2007. Global patterns and determinants of vascular plant diversity. Proceedings of the National Academy of Science, 104: 5925–5930.

    Article  Google Scholar 

  • Kronvang B, Andersen H E, Børgesen C et al., 2008. Effects of policy measures implemented in Denmark on nitrogen pollution of the aquatic environment. Environmental Science & Policy, 11: 144–152.

    Article  Google Scholar 

  • Larson D W, Matthes U, Gerrath J A et al., 2000. Evidence for the widespread occurrence of ancient forests on cliffs. Journal of Biogeography, 27: 319–331.

    Article  Google Scholar 

  • Liang G, Ding S, 2006. Driving factors of forest landscape change in Yiluo River basin. Journal of Geographical Sciences, 16(4): 415–422.

    Article  Google Scholar 

  • Meddens A J H, Hudak A T, Evans J S et al., 2008. Characterizing forest fragments in boreal, temperate, and tropical ecosystems. AMBIO: A Journal of the Human Environment, 37: 569–576.

    Article  Google Scholar 

  • Menard S, 2000. Coefficients of determination for multiple logistic regression analysis. The American Statistician, 54: 17–24.

    Google Scholar 

  • Messerli B, Grosjean M, Hofer T et al., 2000. From nature-dominated to human-dominated environmental changes. Quaternary Science Reviews, 19: 459–479.

    Article  Google Scholar 

  • Nogués-Bravo D, Ajaújo M B, Romdal T et al., 2008. Scale effects and human impact on the elevational species richness gradients. Nature, 453: 216–219.

    Article  Google Scholar 

  • Odgaard B, Nielsen A B, 2009. Udviklingen i arealdækning i perioden 0–1850. Pollen og landskabshistorie. In: Bent Odgaard, Jørgen Rydén Rømer (eds.). Danske landbrugslandskaber gennem 2000 år. Fra digevoldinger til støtteordninger. Denmark, p.41.

    Google Scholar 

  • Odgaard B V, Rasmussen P, 2000. Origin and temporal development of macro-scale vegetation patterns in the cultural landscape of Denmark. Journal of Ecology, 88: 733–748.

    Article  Google Scholar 

  • Pineda Jaimes N B, Bosque Sendra J, Gómez Delgado M et al., 2010. Exploring the driving forces behind deforestation in the state of Mexico (Mexico) using geographically weighted regression. Applied Geography, 30: 576–591.

    Article  Google Scholar 

  • Prentice C, Cramer W, Harrison S P et al., 1992. A global biome model based on plant physiology and dominance, soil properties and climate. Journal of Biogeography, 19: 117–134.

    Article  Google Scholar 

  • R Development Core Team, 2010. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. (http://www.r-project.org/).

    Google Scholar 

  • Rangel T F, Diniz-Filho J A F, Bini L M, 2010. SAM: A comprehensive application for spatial analysis in macroecology. Ecography, 33: 46–50.

    Article  Google Scholar 

  • Reger B, Otte A, Waldhardt R, 2007. Identifying patterns of land-cover change and their physical attributes in a marginal European landscape. Landscape and Urban Planning, 81: 104–113.

    Article  Google Scholar 

  • Rouget M, Richardson D M, Cowling R M, 2003. The current configuration of protected areas in the Cape Floristic Region, South Africa: Reservation bias and representation of biodiversity patterns and processes. Biological Conservation, 112: 129–145.

    Article  Google Scholar 

  • Rygnestad H, Jensen J D, Dalgaard T, 2002. Integrated economic and spatial analyses of afforestration strategies in Denmark. Danish Journal of Geography, 3: 41–48.

    Google Scholar 

  • Scott J M, Davis F W, McGhie R G et al., 2001. Nature reserves: Do they capture the full range of America’s biological diversity? Ecological Applications, 11: 999–1007.

    Article  Google Scholar 

  • Shan J, Toth C K, 2009. Topographic laser ranging and scanning. USA.

    Google Scholar 

  • Sklenicka P, Salek M, 2008. Ownership and soil quality as sources of agricultural land fragmentation in highly fragmented ownership patterns. Landscape Ecology, 23: 299–311.

    Article  Google Scholar 

  • Svenning J, 2002. A review of natural vegetation openness in north-western Europe. Biological Conservation, 104: 133–148.

    Article  Google Scholar 

  • Taillefumier F, Piégay H, 2003. Contemporary land use changes in prealpine Mediterranean mountains: A multivariate GIS-based approach applied to two municipalities in the Southern French Prealps. Catena, 51: 267–296.

    Article  Google Scholar 

  • The Danish Society for Nature Conservation. 2012.

  • Troeh F R, Thompson L M, 2005. Physical properties of soils. In: Frederick R Troeh, Louis M Thompson (eds.). Soils and Soil Fertility. USA, p.37.

    Google Scholar 

  • Vitousek P M, Mooney H A, Lubchenco J et al., 1997. Human domination of earth’s ecosystems. Science, 277: 494–499.

    Article  Google Scholar 

  • Wilson J P, Gallant J C, 2000. Secondary topographic attributes. In: John P Wilson, John C Gallant (eds.). Terrain Analysis, Principles and Applications. USA, p.87.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mette V. Odgaard.

Additional information

Author: Mette Vestergaard Odgaard, PhD Candidate, specialized in landscape dynamics and geographic information science.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Odgaard, M.V., Bøcher, P.K., Dalgaard, T. et al. Human-driven topographic effects on the distribution of forest in a flat, lowland agricultural region. J. Geogr. Sci. 24, 76–92 (2014). https://doi.org/10.1007/s11442-014-1074-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11442-014-1074-6

Keywords

Navigation