Effects of Changing Scale - What Happens When We Look at the Same Location in a Different Way?

What happens when we change grain or extent?

The extent of a scale can be changed independently of grain, that is, a small grain can be maintained as extent increases in size or time (Figure 3) (Turner and Gardner 2015). Grain and extent are often positively correlated, in that, as extent increases so does grain size (Wiens 1989; Turner and Gardner 2015). Changing the scale of observation (extent and/or grain) leads to changes in the variability between observations. For example, when extent is held constant, increasing the grain size results in less variability among observations. This is because fine differences are “smoothed” or averaged when large grain size is used to make observations (Weins 1989). When grain is held constant and extent is increased in non-uniform (i.e., heterogeneous) environments the variation between observations (grain) increases because increasing the extent incorporates more variety within the area or time of interest (Weins 1989). 

Figure 3. Relationships between variability and grain size. As grain size increases, the amount of variation between observations (e.g., plots) decreases (top panel). At the same time, variation within individual grains (e.g., plots) increases with increasing grain size (bottom panel).

Adapted from "Spatial Scaling in Ecology", by Weins, 1989, Functional Ecology, 3(4), 385-397. Copyright JSTOR 1989.

Effects of Scale

Different patterns in nature emerge when the scale is changed. Below we provide examples from the scientific literature. In the examples it is important to remember that scale is associated with both time and space.

Real World Examples

  • In forests of the north-eastern United States, Least Flycatchers negatively influence the distribution of American Redstart (both are bird species) at the extent of 4-ha plots. However, at broad regional extents, these species are positively associated. This is expected to occur because at broad scales habitat suitability for both species overrides the influence of competition between these species at fine scales. Example is from Weins (1989).
  • In the Great Barrier reef, the distribution of fish species at the scale of coral patches is unpredictable due to chance events influencing the occurrence of individual species. However, at broader scales of reef systems, species composition is highly predictable. Example is from Weins (1989).
  • Plant physiologists studying plant transpiration at the scale of individual leaf surfaces have concluded that stomatal mechanisms regulate transpiration. While, meteorologists working at broad scales have concluded that climate is the principal control. Example is from Weins (1989).
  • Similarly, at fine scales litter decomposition rates are explained by the properties of the litter and decomposers, but at larger scales climate variables explain variation in decomposition rates. Example is from Weins (1989).
  • Fine scale studies of cattle grazing in the shortgrass prairie show that cattle select for specific elements of plant communities on the basis of short-term foraging decisions. However, at broader scales, cattle select vegetation types in proportion to their availability within landscapes (i.e., no evidence of preference). Example is from Weins (1989).
  • At finer scales, self-sustaining populations of lesser prairie chickens (shown by white line in figure 4) occurred in areas with more cropland cover compared to declining populations (shown by green line in figure 4). However, at broader scales self-sustaining populations occurred in areas with less cropland cover compared to declining populations (Fig. 4). Example is from Fuhlendorf et al. (2002).
  • “Soil scientists investigating changes in soil organic matter found that different patterns emerged when the temporal scale was changed. An observation window of years (i.e., temporal extent) showed seasonal changes in soil organic matter. While, an observation window of centuries showed long-term increases in soil organic matter tied to successional changes in the plant community. Example is from Sollins et al. (1983).”

Figure 4. Cropland cover at various observational scales surrounding self-sustaining and declining populations of lesser prairie chickens. Points along lines show the amount of cropland cover associated with lesser prairie chicken populations at multiple scales. 

Adapted from "Multi-scale effects of habitat loss and fragmentation on lesser prairie-chicken populations of the US Southern Great Plains," by Fuhlendorf et al., 2002, Landscape Ecology, 17, 617-628. Copyright 2002 by Springer.