Biodiversity and Conservation

, Volume 22, Issue 10, pp 2151–2166 | Cite as

Topographically controlled soil moisture drives plant diversity patterns within grasslands

  • Jesper Erenskjold Moeslund
  • Lars Arge
  • Peder Klith Bøcher
  • Tommy Dalgaard
  • Rasmus Ejrnæs
  • Mette Vestergaard Odgaard
  • Jens-Christian Svenning
Original Paper


Grasslands are recognized as biodiversity hotspots in Europe. However, protection and management of these habitats are currently constrained by a limited understanding of what determines local grassland plant diversity patterns. Here, we combined vegetation records (8,639 inventory plots) from 258 semi-natural grasslands with fine-resolution topographic data based on light detection and ranging technology to investigate the importance of topography—particularly topographically controlled soil moisture—for local and regional grassland plant diversity patterns across a 43,000 km2 lowland region (Denmark). Specifically, we examined the relationships between five vegetation measures representing species composition and richness as well as functional composition (Ellenberg indicator values) and four functional topographic factors representing topographic wetness, potential solar radiation, heat balance and wind exposure. Topography emerged as an important determinant of diversity patterns in both wet and dry grasslands throughout the study region, with topographic wetness being the strongest correlate of the main local (within-site) and regional (among-sites) gradients in species composition and species’ average preferences for soil moisture. Accordingly, topography plays an important role in shaping grassland plant diversity patterns both locally and regionally throughout this lowland European region, with this role mainly driven by topographically controlled soil moisture. These findings suggest hydrology to be important to consider in the planning and management of European grasslands.


Europe Light detection and ranging (LiDAR) Local scale NATURA 2000 Solar radiation Topographic wetness index (TWI) Vegetation Wind 



We thank Bettina Nygaard for help accessing the NOVANA data and gratefully acknowledge funding from the Aarhus University Research Foundation via the Center for Interdisciplinary Geospatial Informatics Research (CIGIR), the Danish Strategic Research Council, Center for Massive Data Algorithmics, a Center of the Danish National Research Foundation, and the Oticon Foundation (grant to J.E.M.).

Supplementary material

10531_2013_442_MOESM1_ESM.pdf (115 kb)
Supplementary material 1 (PDF 114 kb)
10531_2013_442_MOESM2_ESM.pdf (338 kb)
Supplementary material 2 (PDF 338 kb)
10531_2013_442_MOESM3_ESM.pdf (42 kb)
Supplementary material 3 (PDF 41 kb)


  1. Amezaga I, Mendarte S, Albizu I et al (2004) Grazing intensity, aspect, and slope effects on limestone grassland structure. Rangel Ecol Manag 57(6):606–612CrossRefGoogle Scholar
  2. Barbour MG et al (1974) Coastal ecology: Bodega Head. University of California Press, CaliforniaGoogle Scholar
  3. Bennie J, Hill MO, Baxter R et al (2006) Influence of slope and aspect on long-term vegetation change in British chalk grasslands. J Ecol 94(2):355–368CrossRefGoogle Scholar
  4. Bennie J, Huntley B, Wiltshire A et al (2008) Slope, aspect and climate: spatially explicit and implicit models of topographic microclimate in chalk grassland. Ecol Model 216(1):47–59CrossRefGoogle Scholar
  5. Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Sci Bull 24(1):43–69CrossRefGoogle Scholar
  6. Bivand R, Altman M, Anselin L et al (2012) Spdep: spatial dependence: weighting schemes, statistics and models. Accessed 19 June 2012
  7. Boose ER, Foster DR, Fluet M (1994) Hurricane impacts to tropical and temperate forest landscapes. Ecol Monogr 64(4):369–400CrossRefGoogle Scholar
  8. Bruun HH, Ejrnæs R (1998) Overdrev–en beskyttet naturtype. Ministry of energy & environment, the forest & nature agency, CopenhagenGoogle Scholar
  9. Burke IC, Lauenroth WK, Vinton MA et al (1998) Plant-soil interactions in temperate grasslands. Biogeochem 42(1):121–143CrossRefGoogle Scholar
  10. Cantlon JE (1953) Vegetation and microclimates on north and south slopes of Cushetunk Mountain. New Jersey. Ecol Monogr 23(3):241–270CrossRefGoogle Scholar
  11. Cappelen J, Jørgensen B (1999) Observed wind speed and direction in Denmark–with climatological standard normals, 1961–90. Danish Meteorological Institute, CopenhagenGoogle Scholar
  12. Collins SL, Knapp AK, Briggs JM et al (1998) Modulation of diversity by grazing and mowing in native tallgrass prairie. Science 280(5364):745–747PubMedCrossRefGoogle Scholar
  13. Commission of the European communities (2002) Commission working document on NATURA 2000. The commission of the European communities, EUGoogle Scholar
  14. Council of the European Communities (1992) Council directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and floraGoogle Scholar
  15. Eckhardt K, Ulbrich U (2003) Potential impacts of climate change on groundwater recharge and streamflow in a central European low mountain range. J Hydrol 284(1–4):244–252CrossRefGoogle Scholar
  16. Eiserhardt WL, Svenning J, Kissling WD et al (2011) Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales. Ann Bot 108(8):1391–1416PubMedCrossRefGoogle Scholar
  17. Ejrnæs R, Bruun HH (2000) Gradient analysis of dry grassland vegetation in Denmark. J Veg Sci 11(4):573–584CrossRefGoogle Scholar
  18. Ellenberg H, Weber HE, Düll R et al (2001) Zeigerwerte von planzen in Mitteleuropa. Erich Goltze GmbH & Co KG, GöttingenGoogle Scholar
  19. Ellermann T, Fenger J, Hertel O et al (2007) Luftbåren kvælstofforurening. Hovedland, AarhusGoogle Scholar
  20. Ennos AR (1997) Wind as an ecological factor. Trends Ecol Evol 12(3):108–111PubMedCrossRefGoogle Scholar
  21. Flanagan LB, Johnson BG (2005) Interacting effects of temperature, soil moisture and plant biomass production on ecosystem respiration in a northern temperate grassland. Agric For Meteorol 130(3–4):237–253CrossRefGoogle Scholar
  22. Freckleton RP (2002) On the misuse of residuals in ecology: regression of residuals vs. multiple regression. J Anim Ecol 71(3):542–545CrossRefGoogle Scholar
  23. Fritzbøger B, Odgaard B (2010) Skovenes historie. In: Møller PF (ed) Naturen i Danmark–Skovene, 1st edn. Gyldendal, CopenhagenGoogle Scholar
  24. Gates DM (1980) Biophysical ecology. Springer, The NetherlandsGoogle Scholar
  25. Gibson DJ (2009) Grasses and grassland ecology. Oxford University Press, New YorkGoogle Scholar
  26. Giesler R, Högberg M, Högberg P (1998) Soil chemistry and plants in Fennoscandian boreal forest as exemplified by a local gradient. Ecology 79(1):119–137CrossRefGoogle Scholar
  27. Grytnes JA (2003) Species-richness patterns of vascular plants along seven altitudinal transects in Norway. Ecography 26(3):291–300CrossRefGoogle Scholar
  28. Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135(2–3):147–186CrossRefGoogle Scholar
  29. Hansson M, Fogelfors H (2000) Management of a semi-natural grassland; results from a 15-year-old experiment in southern Sweden. J Veg Sci 11(1):31–38CrossRefGoogle Scholar
  30. Hill MO, Mountford JO, Roy DB et al (1999) Ellenberg’s indicator values for British plants. ECOFACT research report series vol 2 technical annex. Institute of Terrestrial Ecology, HuntingdonGoogle Scholar
  31. Janssens F, Peeters A, Tallowin JRB et al (1998) Relationship between soil chemical factors and grassland diversity. Plant Soil 202(1):69–78CrossRefGoogle Scholar
  32. Kissling WD, Carl G (2008) Spatial autocorrelation and the selection of simultaneous autoregressive models. Global Ecol Biogeogr 17(1):59–71Google Scholar
  33. Knapp AK (1985) Early season production and microclimate associated with topography in a C4 dominated grassland. Acta Oecol 6(20):337–345Google Scholar
  34. Kopecký M, Čížková Š (2010) Using topographic wetness index in vegetation ecology: does the algorithm matter? Appl Veg Sci 13(4):450–459CrossRefGoogle Scholar
  35. Landolt E, Bäumler B, Erhardt A et al (2010) Flora indicativa–ökologische zeigerwerte und biologische kennzeichen zur flora der Schweiz und der Alpen. Haupt, BernGoogle Scholar
  36. Legendre P, Legendre L (1998) Numerical ecology. Elsevier, New YorkGoogle Scholar
  37. Li F, Zhao L, Zhang H et al (2009) Habitat degradation, topography and rainfall variability interact to determine seed distribution and recruitment in a sand dune grassland. J Veg Sci 20(5):847–859CrossRefGoogle Scholar
  38. Loiseau P, Louault F, Le Roux X et al (2005) Does extensification of rich grasslands alter the C and N cycles, directly or via species composition? Basic Appl Ecol 6(3):275–287CrossRefGoogle Scholar
  39. Maskell LC, Smart SM, Bullock JM et al (2010) Nitrogen deposition causes widespread loss of species richness in British habitats. Global Change Biol 16(2):671–679CrossRefGoogle Scholar
  40. McCune B, Keon D (2002) Equations for potential annual direct incident radiation and heat load. J Veg Sci 13(4):603–606CrossRefGoogle Scholar
  41. Mikita T, Klimánek M (2010) Topographic exposure and its practical applications. J Landscape Ecol 3(1):42–51Google Scholar
  42. Moeslund JE, Arge L, Bøcher P et al (2011) Geographically comprehensive assessment of salt-meadow vegetation-elevation relations using LiDAR. Wetlands 31:471–482CrossRefGoogle Scholar
  43. Mossberg B, Stenberg L (2005) Den nye nordiske Flora. Gyldendal, CopenhagenGoogle Scholar
  44. Narum SR (2006) Beyond Bonferroni: less conservative analyses for conservation genetics. Conserv Genet 7:783–787CrossRefGoogle Scholar
  45. National Survey and Cadastre (2008) Proceedings of the 2nd NKG workshop on national DEMs, Copenhagen, 11–13 Nov 2008Google Scholar
  46. Økland RH, Rydgren K, Økland T (2008) Species richness in boreal swamp forests of SE Norway: the role of surface microtopography. J Veg Sci 19(1):67–74CrossRefGoogle Scholar
  47. Oksanen J, Blanchet FG, Kindt R et al. (2011) Vegan: community ecology package. Accessed 19 June 2012
  48. Olivero AM, Hix DM (1998) Influence of aspect and stand age on ground flora of southeastern Ohio forest ecosystems. Plant Ecol 139(2):177–187CrossRefGoogle Scholar
  49. Parker J (1952) Environment and forest distribution of the Palouse Range in Northern Idaho. Ecology 33:451–461Google Scholar
  50. Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecol Biog 12(5):361–371CrossRefGoogle Scholar
  51. Perring F (1959) Topographical gradients of chalk grassland. J Ecol 47(2):447–481CrossRefGoogle Scholar
  52. Quinn P, Beven K, Chevallier P et al (1991) The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. Hydrol Process 5(1):59–79CrossRefGoogle Scholar
  53. R Development Core Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  54. Reitalu T, Johansson LJ, Sykes MT et al (2010) History matters: village distances, grazing and grassland species diversity. J Appl Ecol 47(6):1216–1224CrossRefGoogle Scholar
  55. Rodriguez-Iturbe I, D’Odorico P, Porporato A et al (1999) On the spatial and temporal links between vegetation, climate, and soil moisture. Water Resour Res 35(12):3709–3722CrossRefGoogle Scholar
  56. Saunders DA, Hobbs RJ, Margules CR (1991) Biological consequences of ecosystem fragmentation: a review. Conserv Biol 5(1):18–32CrossRefGoogle Scholar
  57. Silvertown J, Dodd ME, Gowing DJG et al (1999) Hydrologically defined niches reveal a basis for species richness in plant communities. Nature 400(6739):61–63CrossRefGoogle Scholar
  58. Stevens CJ, Dise NB, Mountford JO et al (2004) Impact of nitrogen deposition on the species richness of grasslands. Science 303(5665):1876–1879PubMedCrossRefGoogle Scholar
  59. Suggitt AJ, Gillingham PK, Hill JK et al (2011) Habitat microclimates drive fine-scale variation in extreme temperatures. Oikos 120(1):1–8CrossRefGoogle Scholar
  60. Svendsen LM, van der Bijl L, Boutrup S et al. (2005) NOVANA. National monitoring and assessment programme for the aquatic and terrestrial environments: programme description–part 2. National Environmental Research Institute, DenmarkGoogle Scholar
  61. Svenning J (1999) Microhabitat specialization in a species-rich palm community in Amazonian Ecuador. J Ecol 87(1):55–65CrossRefGoogle Scholar
  62. Svenning J (2001) On the role of microenvironmental heterogeneity in the ecology and diversification of neotropical rain-forest palms (Arecaceae). Bot Rev 67(1):1–53CrossRefGoogle Scholar
  63. Vázquez JA, Givnish TJ (1998) Altitudinal gradients in tropical forest composition, structure, and diversity in the Sierra de Manantlán. J Ecol 86(6):999–1020CrossRefGoogle Scholar
  64. Vierling KT, Vierling LA, Gould WAG et al (2008) Lidar: shedding new light on habitat characterization and modelling. Front Ecol Environ 6(2):90–98CrossRefGoogle Scholar
  65. Vivian-Smith G (1997) Microtopographic heterogeneity and floristic diversity in experimental wetland communities. J Ecol 85(1):71–82CrossRefGoogle Scholar
  66. Willis KJ, Whittaker RJ (2002) Species diversity-scale matters. Science 295(5558):1245–1248PubMedCrossRefGoogle Scholar
  67. Wilson JP, Galant JC (2000) Terrain analysis: principles and applications. Wiley, New YorkGoogle Scholar
  68. Zavaleta ES, Pasari JR, Hulvey KB et al (2010) Sustaining multiple ecosystem functions in grassland communities requires higher biodiversity. Proc Natl Acad Sci 107(4):1443–1446PubMedCrossRefGoogle Scholar
  69. Zinko U, Dynesius M, Nilsson C et al (2006) The role of soil pH in linking groundwater flow and plant species density in boreal forest landscapes. Ecography 29(4):515–524CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Jesper Erenskjold Moeslund
    • 1
    • 2
    • 3
  • Lars Arge
    • 2
  • Peder Klith Bøcher
    • 1
  • Tommy Dalgaard
    • 3
  • Rasmus Ejrnæs
    • 4
  • Mette Vestergaard Odgaard
    • 1
    • 3
  • Jens-Christian Svenning
    • 1
  1. 1.Ecoinformatics & Biodiversity Group, Department of BioscienceAarhus UniversityAarhus CDenmark
  2. 2.Center for Massive Data Algorithmics (MADALGO), Department of Computer ScienceAarhus UniversityAarhus NDenmark
  3. 3.Agricultural Systems and Sustainability, Department of AgroecologyAarhus UniversityTjeleDenmark
  4. 4.Wildlife Ecology and Biodiversity, Department of BioscienceAarhus UniversityRøndeDenmark

Personalised recommendations