Linking Fine-Scale Sub-Arctic Vegetation Distribution in Complex Topography with Surface-Air-Temperature Modelled at 50-m Resolution
- 307 Downloads
Recent studies have shown that the complexities of the surface features in mountainous terrain require a re-assessment of climate impacts at the local level. We explored the importance of surface-air-temperature based on a recently published 50-m-gridded dataset, versus soil variables for explaining vegetation distribution in Swedish Lapland using generalised linear models (GLMs). The results demonstrated that the current distribution of the birch forest and snowbed community strongly relied on the surface-air-temperature. However, temperature alone is a poor predictor of many plant communities (wetland, meadow). Because of diminishing sample representation with increasing altitude, the snowbed community was under-sampled at higher altitudes. This results in underestimation of the current distribution of the snowbed community around the mountain summits. The analysis suggests that caution is warranted when applying GLMs at the local level.
KeywordsGeneralised linear model Mountains Vegetation distribution Swedish sub-arctic Scale
This study was conducted as part of the Marie Curie Early Stage Training network—Multiarc-supported by European Union FP7. This study was also partially supported by FORMAS projects “Climate change, impacts and adaptation in the sub-Arctic: a case study from the northern Swedish mountains” (214-2008-188) and “Advanced Simulation of Arctic climate change and impact on Northern regions” (214-2009-389). The authors wish to thank two anonymous reviewers for their comments. The authors are grateful to Eva Kuster, Jonas Åkerman, Christer Jonasson, and Jonathon Seaquist for valuable comments. We would like to thank Paul Coles for his help to redraw the graphs. We would like to thank Abisko Scientific Research Station staff for help and data collection.
- Akaike, H. 1973. Information theory as an extension of the maximum likelihood principle. Paper presented at the 2nd international symposium on information theory, Akademiai Kiado. Budapest, Hungary.Google Scholar
- Araújo, M.B., W. Thuiller, and N.G. Yoccoz. 2009. Reopening the climate envelope reveals macroscale associations with climate in European birds. Proceedings of the National academy of Sciences of the United States of America 106: E45–E46.Google Scholar
- Callaghan, T.V., and P.S. Karlsson. 1996. Plant ecology in subarctic Swedish Lapland: Summary and conclusions. Ecological Bulletins 45: 220–227.Google Scholar
- Chevan, A., and M. Sutherland. 1991. Hierarchical partitioning. The American Statistician 45: 90–96.Google Scholar
- Desdevises, Y., P. Legendre, L. Azouzi, and S. Morand. 2003. Quantifying phylogenetically structured environmental variation. Evolution 57: 2647–2652.Google Scholar
- Franklin, J. 2009. Mapping species distributions: Spatial inference and prediction. Cambridge: Cambridge University Press.Google Scholar
- Freeman, E. 2007. PresenceAbsence: An R Package for Presence-Absence Model Evaluation, USDA Forest Service.Google Scholar
- Grau, O., J.M. Ninot, J.M. Blanco-Moreno, R.S.P. van Logtestijn, J.H.C. Cornelissen, and T.V. Callaghan. 2012. Shrub-tree interactions and environmental changes drive treeline dynamics in the Subarctic. Oikos. doi: 10.1111/j.1600-0706.2011.20032.x.
- Lang, S.I., J.H.C. Cornelissen, A. Hölzer, C.J.F. Ter Braak, M. Ahrens, T.V. Callaghan, and R. Aerts. 2009. Determinants of cryptogam composition and diversity in Sphagnum-dominated peatlands: The importance of temporal, spatial and functional scales. Journal of Ecology 97: 299–310. doi: 10.1111/j.1365-2745.2008.01472.x.CrossRefGoogle Scholar
- Rodhe, L., M. Pyykonen, and M. Krekula. 1999. Jordartskarta: Geological Survey of Sweden.Google Scholar
- Tomas, P. 1998. Fjällvegetation, vektorformat för 30I (Abisko). Metria, Lantmäteriet GSD.Google Scholar
- Van Bogaert, R., K. Hanece, J. Hoogesteger, C. Jonasson, M.D. Dapper, and T.V. Callaghan. 2011. A century of tree line changes in sub-Arctic Sweden shows local and regional variability and only a minor influence of 20th century climate warming. Journal of Biogeography 38: 907–921.CrossRefGoogle Scholar
- Walsh, C., and R Mac Nally. 2003. The hier.part Package: Hierarchical Partitioning. (Part of: Documentation for R: A language and environment for statistical computing.)Google Scholar
- Zhenlin, Y., E. Hanna, and T.V. Callaghan. 2011. Modelling surface-air-temperature variation over complex terrain around Abisko, Swedish Lapland: Uncertainties of measurements and models at different scales. Geografiska Annaler: Series A, Physical Geography 93: 89–112. doi: 10.1111/j.1468-0459.2011.00005.x.CrossRefGoogle Scholar
- Zhenlin, Y., E. Hanna, T.V. Callaghan, and C. Jonasson. 2012. How can meteorological observations and microclimate simulations improve understanding of 1913–2010 climate change around Abisko, Swedish Lapland? Meteorological Applications. doi: 10.1002/met.276.