The Integration of Scales in Landscape Ecology

Inquiries into the issue of scale become increasingly important in the field of landscape ecology and natural resource modelling and analysis. Scales of observation and modelling are often pre-set based on the a priori description of the system of study. In this paper we focus on upscaling approaches. We emphasize that predictability depends on the relation between the spatial and the temporal scale of study. Three examples of scale dependent processes illustrate the importance of identifying the scale at which processes operate to avoid erroneous conclusions. Two modelling studies show a number of scale related bottlenecks in data, interpolation, extrapolation and modelling. In statistical modelling of spatial data spatial dependence should be examined, truly independent validation data sets should be available and spatial extrapolation should be done with care. In mechanistic modelling of processes spatial up-scaling requires information on landscape heterogeneity and how this influences the modelled processes. Although a general guideline in choosing an appropriate scale of study is that discrepancies between the scale of observation, dominant processes and model calculations should be avoided, in most landscape ecological studies such discrepancies are a given. They should be explicitly acknowledged and the information in this paper may help in recognizing them and dealing with them.