Abstract
As a starting point GIS (geographical information systems) seem intuitively to be a practical tool for biologists performing ecological research. GIS conveniently stores, explores, analyses and visualizes biological/ecological/environmental observations. A thorough exploration of the opportunities offered by GIS was made in twelve different Norwegian ecological studies. These studies span scales from the regional at which biogeographical patterns can be studied, to centimetre-scales at which the fates of small (bryophyte) individuals may be followed. They encompass different ecosystems – marine, freshwater and terrestrial. They target animal, fungi and plants. More than 300 vascular plant species, 150 bryophytes species, 50 lichen species, 150 fungi species and 100 zooplankton species were included in the studies in addition to two species of butterflies and one seal species. GIS was an efficient tool for handling variation in data properties in all studies that opened many new opportunities. The most promising new scientific results from the GIS analyses were perhaps the least-cost path modelling for actual movement and dispersal of organisms in a landscape, the development of objective, step-less models for biogeographical variation and spatial prediction modelling of species occurrence and diversity patterns. However, concern is raised that the rather high user threshold of GIS software [and the recurrent needs for data programming (scripting)] prevents many scientists from using GIS in their own ecological research. The importance of being able to address different spatial and temporal scales in all kinds of ecological research is also discussed. Scale is easily handled in GIS. Most notably, two of the most critical questions in spatial pattern analysis can be analysed through geostatistical GIS tools: determination of the appropriate scale to conduct the analysis; and to assess the nature (and strength) of the spatial structure. A two-stage strategy, comprising biogeographical analysis of the distributions of species by use of sampling units that span the main regional gradients, and a local ecological approach to the abundance variation of the species, seems to be a most fruitful analytic strategy. This study also underpins the everlasting need for including baseline investigations (identification of patterns of variation in species composition, followed by ecological interpretation) in ecological studies irrespective of scale, environment and species. The included monitoring approaches showed condiderable variation occurs over short time periods, even in apparently stable ecosystems. Monitoring projects are therefore important for the understanding of important processes and present condition in ecosystems. Both baseline investigations and monitoring projects is this thesis is thus crucial for be one of the main targets for ecological research in coming years: prediction of what will happen to species and ecosystems under different environmental (including climate) change scenarios. In this context, GIS seems an inevitably important tool.
List of papers
PAPER 1: Bakkestuen, V., Erikstad, L., & Halvorsen, R. 2008. Step-less models for regional environmental variation in Norway. Journal of Biogeography 35: 1906-1922. The published version of this paper is available at: https://doi.org/10.1111/j.1365-2699.2008.01941.x |
PAPER 2: Bakkestuen, V., Aarrestad, P.A., Stabbetorp, O.E., Erikstad, L. & Eilertsen, 0. 2008. Vegetation composition, gradients and environment relationships of birch forest in six monitoring reference areas in Norway. Sommerfeltia 33 (in press) |
PAPER 3: Bakkestuen, V., Halvorsen, R. & Heegaard, E. 2009. Disentangling complex fine-scaled ecological patterns by path modeling, using GLMM and GIS. Journal of Vegetation Science Journal of Vegetation Science 20: 779-790. The published version of this paper is available at: https://doi.org/10.1111/j.1654-1103.2009.01001.x |
PAPER 4: Bekkby, T., Erikstad, L., Bakkestuen, V. & Bjørge, A. 2002. A landscape ecological approach to coastal zone applications. Sarsia 87: 396-408. The published version of this paper is available at: https://doi.org/10.1080/0036482021000155845 |
PAPER 5: Bekkby, T., Rinde, E., Erikstad, L., Bakkestuen, V., Longva, O., Christensen, O., Isæus, M. & Isachsen, P.E. 2008. Spatial probability modelling of eelgrass Zostera marina L. distribution on the West coast of Norway. ICES Journal of Marine Science 65: 1093-1101. The published version of this paper is available at: https://doi.org/10.1093/icesjms/fsn095 |
PAPER 6: Bendiksen, E., Økland, R.H., Høiland, K., Eilertsen, O. & Bakkestuen, V. 2005. Relationships between macrofungi, vegetation and environmental factors in boreal coniferous forests in the Solhomfjell area, Gjerstad, S Norway. Sommerfeltia 30: 1-125. |
PAPER 7: Hessen, D.O., Faafeng, B.A., Smith, V.H., Bakkestuen, V. & Walseng, B. 2006. Extrinsic and intrinsic controls of zooplankton diversity in lakes. Ecology 87: 433-443. The published version of this paper is available at: https://doi.org/10.1890/05-0352 |
PAPER 8: Hessen, D.O., Bakkestuen, V. & Walseng, B. 2007. Energy input and zooplankton diversity. Ecography 30: 749-758. The published version of this paper is available at: https://doi.org/10.1111/j.2007.0906-7590.05259.x |
PAPER 9: Økland, R. H. & Bakkestuen, V. 2004. Fine-scale spatial patterns in populations of the clonal moss Hylocomium splendens partly reflect structuring processes in the boreal forest floor. Oikos 106: 565-575. The published version of this paper is available at: https://doi.org/10.1111/j.0030-1299.2004.12574.x |
PAPER 10: Økland, T., Bakkestuen, V., Økland, R.H. & Eilertsen, O. 2004. Changes in forest understory vegetation in Norway related to long-term soil acidification and climatic change. Journal of Vegetation Science 15: 437-448.Journal of Vegetation Science 15: 437-448. The published version of this paper is available at: https://doi.org/10.1111/j.1654-1103.2004.tb02282.x |
PAPER 11: Sutcliffe, O.L., Bakkestuen, V., Fry, G.L.A. & Stabbetorp., O.E. 2003. Modelling the benefits of farmland restoration: Methodology and application to butterfly movement. Landscape and Urban Planning 63: 15-31. The published version of this paper is available at: https://doi.org/10.1016/S0169-2046(02)00153-6 |
PAPER 12: Wollan, A. K., Bakkestuen, V., Kauserud, H., Gulden., G & Halvorsen, R. 2008. Modelling and predicting fungal distribution patterns using herbarium data. Journal of Biogeography 35: 2298-2310. The published version of this paper is available at: https://doi.org/10.1111/j.1365-2699.2008.01965.x |