Influence of scale on system performance and outcomes

Scales are the topographical instruments used to divide objects or processes into levels of organization of space or time and to distinguish objects within, for instance, a biotic hierarchy. Scale is designed by using grain and extent. Grain refers to the spatial resolution within a particular data set e.g. The cell size for gridded maps whilst extant refers to the overall size of the map used to demonstrate temporarily and dimension of characteristic. A population, pattern, or process that is scale-dependent implies that the object under consideration is correlated with the scale, i.e. changes with the grain or extent of measurement. "Large scale' refers to extremely fine resolution (i.e. precision of measurement), whereas 'small scale' refers to the opposite.

Scales are both advantageous and disadvantageous when applied to ecology and to environmental concerns. On the one hand, ecological variables demonstrate numerous and multiple change and knowing where one environment or habitat begins and where the other ends is difficult. They cannot be measured in the same way as humans and, consequently, different scales must be devised.

Making the scale and assigning the pattern, process, or organism to the scale is, furthermore, problematic since the scale at which the scientist makes the measurement, for instance the size of the grid cell or the size of the quadrant influences the numerical answer obtained. One instance of this was the incident of the species-area curve where ecologists soon realized that the number of species detected increased asymptotically (i.e. did not intersect with the given curve) according to the grid of the scale.

Another problem is our difference between absolute and relative time and distance and that of the organism under study. What may seem absolute time to us can be measured in different segments from the perspective, let's say of the crow under study. Extrapolating from the human mindset, therefore, may be erroneous. Extrapolation is particularly problematic in nonlinear cases when sudden changes in quality, property, or phenomenon (i.e. critical thresholds) make it difficult to classify.

Other problems include the three identified by Haggart, namely: (a) the scale coverage problem: where the surface of the Earth is so large that it is difficult to map and understand its spatial variability; (b) the scale linkage problem: where fieldwork, being generally confined to small areas, makes it difficult to extrapolate to larger, or other, tracts; (c) scale standardization problems: researchers may employ differing methods in collecting and reporting data. Extrapolating from one to another may be confusing and misleading.