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Recent Developments in Spatial Methods and Data in Biogeographical Distribution Modelling – Advantages and Pitfalls

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Recent Developments in Spatial Methods and Data in Biogeographical Distribution Modelling – Advantages and Pitfalls Recent developments in spatial methods and data in biogeographical distribution modelling – advantages and pitfalls MISKA LUOTO AND RISTO HEIKKINEN Luoto, Miska & Risto Heikkinen (2003). Recent developments in spatial meth- ods and data in biogeographical distribution modelling – advantages and pit- falls. Fennia 181: 1, pp. 35–48 Helsinki. ISSN 0015-0010. Geography has a long tradition in studies of geographical distribution of flora and fauna. Detailed mappings of the distributions of biota over wide regions can produce highly valuable biogeographical data, but are extremely labori- ous. These challenges in biogeographical mapping, as well as the need for mitigation tools for the adverse impacts of human disturbance on the land- scape and biodiversity, have stimulated the development of new approaches for assessing biogeographical patterns. Particularly, the ability to model distri- bution patterns of organisms and habitat types has recently increased along with the theoretical and methodological development of biogeography and spatial ecology, and modern spatial techniques and extensive data sets (pro- vided e.g., by earth observation techniques). However, geographical data have characteristics which produce statistical problems and uncertainties in these modelling studies: 1) the data are almost always multivariate and intercorre- lated, 2) the data are often spatially autocorrelated, and 3) biogeographical distribution patterns are affected by different factors operating on different spa- tial and temporal scales. Especially remote sensing and geographic informa- tion data provide powerful means for studies of environmental change, but also include pitfalls and may generate biased results. Quantitative analysis and modelling with correct and strict use of spatial statistics should also receive more attention. The issues discussed in this paper can have relevance in sev- eral fields of application of geographical data. Miska Luoto & Risto Heikkinen, Finnish Environment Institute, Research Pro- gramme for Biodiversity, P.O. Box 140, FIN-00251 Helsinki, Finland. E-mail: [email protected], [email protected]. MS submitted 8 No- vember 2002. Introduction et al. 1995; Huxel & Hastings 1999; Noss 2001; Fahrig 2002; Schmielgelow & Mönkkönen 2002; Spatial patterning and distribution of organisms see also Watson 2002). This development has giv- has traditionally attracted much interest and has en rise to increasing concern about the potential stimulated research in geography. Consequently, loss of important natural values and has inspired issues such as which environmental factors ex- a development of new techniques to map and plain the distribution of various plants has con- monitor wide areas of land. Such techniques are tinuously had a central role in biogeographical clearly urgently required to analyse and model research since the pioneering work of Alexander human-based impacts on landscape and biodiver- von Humboldt in the early 19th century (von sity (Griffiths et al. 1993). The technical tools and Humboldt 1807; Turner 1989). theoretical framework needed in the modelling of Nowadays, the spatial distribution of organisms spatial distribution of species in landscapes have is also strongly affected by the adverse impacts actually improved due to the recent methodolog- of human disturbance, particularly habitat loss ical developments in biogeography and spatial and fragmentation (Tilman et al. 1994; Enoksson ecology, as well as in statistical methods and spa- 36 Miska Luoto and Risto Heikkinen FENNIA 181: 1 (2003) tial data analysis (Scott et al. 1993; Stoms & Estes landscape ecology constantly face, and moreover, 1993; Hanski 1998; Debinski et al. 1999; Guisan similar questions are also of importance in other & Zimmermann 2000; Roy & Tomar 2000). fields of geography. Thus, the ideas presented here However, the integration of geographical anal- are applicable in several other fields of study ysis and modelling and GI (geographic informa- where geographical data are applied. tion) technology and spatial data from different sources requires transdisciplinary skills between geography, ecology, statistics and social sciences. Benchmarks in the development of Thus the pitfalls for the misuse of GIS technology biogeography and spatial ecology with its high calculation capacity are very obvi- ous. Several recent papers dealing with spatial In 1807, von Humboldt described the latitudinal data have highlighted the fact that the correct use and altitudinal distribution of vegetative zones. of spatial statistics with GI and RS (remotely His work ’Ideen zu einer Geographie der Pflan- sensed) data is increasingly important (Stoms zen nebst einem Naturgemälde der Tropenländer’ 1992; Luoto 2000a; Liebhold & Gurevitch 2002; provided an inspiration to studies of the geograph- Perry et al. 2002). ic distribution of plants and animals. Throughout Geographical data sets have several character- the 19th century, botanists and zoologists de- istics which separate them from many other kinds scribed and explained the spatial distributions of of data sets. These features produce severe statis- various taxa mainly by macroclimatic factors such tical problems and uncertainties in the modelling as temperature and precipitation (Turner 1989; studies of biogeographical distribution data. First, Granö & Paasi 1997). spatial data are almost always multivariate, i.e. The emerging view was that strong interde- there are more than one variate or analyte of in- pendencies between climate, biota, and soil lead terest, which are correlated to some degree. Sec- to long-term stability of the landscape in the ab- ond, the spatial location of each data point can sence of climatic changes. The early biogeograph- be described by its geographic coordinates. This ical studies also influenced Clements’ theory (Cle- positional association is often also manifested in ments 1936) of successional dynamics, in which another way, namely through some form of spa- the stable endpoint, the climax vegetation, was tial correlation (Legendre 1993; Brito et al. 1999). determined by macroclimate over a broad region. Thirdly, distribution patterns and processes are Clements stressed temporal dynamics but did not often affected by different factors operating on dif- emphasise spatial patterning. The development of ferent scales. Spatial systems generally show char- gradient analysis (Whittaker 1967) allowed de- acteristic variability on a range of spatial, tempo- scription of the continuous distribution of species ral and organizational scales and therefore, there along environmental gradients. Abrupt disconti- is no single natural scale on which geographical nuities in vegetation patterns were believed to be phenomena should be studied (see Wiens 1989; associated with discontinuities in the physical Levin 1992; Stoms 1994). environment. Many of the above-mentioned problems are Watt (1947) first linked space and time on a currently topical in geography, especially in stud- broader scale in biogeography. He described the ies with GI and RS data sets (Högmander & Møller distribution of the entire temporal progression of 1995; Augustin et al. 1996). This paper does not successional stages as a pattern of patches across aim at representing a fully comprehensive review a landscape. The complex spatial pattern across covering all the relevant issues and their back- the landscape was constant, but this constancy in grounds in contemporary geographical data min- the pattern was maintained by temporal changes ing, analysis and modelling. Instead, we focus in at each point. The modern concept of the shifting this commentary paper on some selected key is- steady-state mosaic, which incorporates natural sues in the development of biogeography and disturbance process, is related to Watt’s concep- landscape ecology, and particularly on the possi- tualisation (Turner 1989). bilities and potential pitfalls of analysing and The interest of biogeographers in spatial aspects modelling spatial data, which are attracting in- increased after the introduction of the theory of creasing attention. Many of the methodological island biogeography by MacArthur & Wilson issues and problems touched upon in this paper (1967). The new theory explained how distance are those which researchers in biogeography and and area together regulate the balance between FENNIA 181: 1 (2003) Recent developments in spatial methods and data in … 37 immigration and extinction in island populations. out any environmental heterogeneity (Tilman & The three basic characteristics of insular biotas Kareiva 1997). By contrast, landscape ecologists are: 1) the number of species increases with in- have been occupied by descriptions of the gener- creasing island size, 2) the number of species de- ally complex physical structure of real environ- creases with increasing distance to the nearest ments, distribution of resources in landscapes, continent or other source of species, and 3) a con- and the movements of individuals (Forman 1995; tinual turnover in species composition occurs, Wiens 1997). Metapopulation ecology makes the owing to recurrent colonisations and extinctions, simplifying assumption that suitable habitat patch- but the number of species remains approximate- es for the focal species occur as a network of ide- ly the same. MacArthur and Wilson (1967) pro- alised habitat patches varying in area, degree of posed that the number of species inhabiting an isolation and quality and surrounded by uniformly island represents
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