MULTISCALE SOURCES OF VARIATION IN ECOLOGICAL VARIABLES - MODELING SPATIAL-DISPERSION, ELABORATING SAMPLING DESIGNS

Detection of structured spatial variation and identification of spatia l scales are important aspects of ecological studies. Spatial structur es can correspond to physical features of the environment or to intrin sic characteristics of ecological processes and phenomena. Spatial var iability has been approached through several techniques such as classi cal analysis of variance, or the calculation of fractal dimensions, co rrelograms or variograms. Under certain assumptions, these techniques are all closely related to one another and represent equivalent tools to characterize spatial structures. Our perception of ecological varia bles and processes depends on the scale at which variables are measure d. We propose simple nested sampling designs enabling the detection of a wide range of spatial structures that show the relationships among nested spatial scales. When it is known that the phenomenon under stud y is structured as a nested series of spatial scales, this provides us eful information to estimate suitable sampling intervals, which are es sential to establish the relationships between spatial patterns and ec ological phenomena. The use of nested sampling designs helps in choosi ng the most suitable solutions to reduce the amount of random variatio n resulting from a survey. These designs are obtained by increasing th e sampling intensity to detect a wider spectrum of frequencies, or by revisiting the sampling technique to select more representative sampli ng units.