Due to the spatial variability in soil properties, multi-scale studies in the context of scale issue is necessary to reveal the complex relationship operating at different intensities.
Examples include the development of nested multi-scale studies and experiments conducted over large spatio-temporal scales at the level of estuary or region.
However, most multi-scale studies choose observational scales using criteria unrelated to how metrics quantify along the scale continuum; scale choice is either arbitrary or via orders of resource selection irrespective of potential among-scale differences in mean or variation.
Multi-scale studies ostensibly allow us to form generalizations regarding the importance of scale in understanding ecosystem function, and in the application of the same ecological principles across a series of spatial domains.
Multi-scale studies allow evaluating the relative role of patch-scale versus landscape-scale factors on species distribution allowing the identification of the spatial scale toward which conservation and management actions should be targeted.
Achieving such generalizations, however, requires consistency among multi-scale studies not only in across-scale sample design, but also in basic rationales used in the choice of observational scale, including both grain and extent.
Based on previous nano- and multi-scale studies at Northwestern, the strength distribution of each link, characterizing the interlamellar shear bond, is assumed to be a Gauss-Weibull graft, but with a deeper Weibull tail than in Type 1 failure of non-imbricated quasibrittle materials.
Multi-scale studies can help reduce this uncertainty by investigating how biodiversity responses scale from the small scale of manipulative experiments (i.e., 10-ha plots) to operational forest management and how biodiversity response to CWD levels might vary at different spatial and temporal scales and in different landscape contexts.
Glacial geomorphologists have used GIS to integrate multi-source data, manage multi-scale studies, identify previously unrecognized spatial and temporal relationships and patterns in geomorphic data, and to link landform data with numerical models as part of model calibration and verification.
Multi-scale studies facilitate an improved understanding of how scale can influence ecosystem functions (Wheatley and Johnson 2009).
One issue with multi-scale studies is the selection of an appropriate set of scales based on the biology of the species.
