We Must Regard Scaling Not Just As a Bothersome Feature of Study Design

Landscape Ecology Scale

"...we must regard scaling not just as a bothersome feature of study design but as a subject meriting study in its own right..." (Wiens 1992)

Terms/people: scale (colloquial vs. cartographic definitions) grain extent extrapolation, interpolation Davies et al. 2001 Roth et al. 1996 With 1993 scaling domains of scale (Krummel et al. 1987)

Scale in ecology -

"The problem of pattern and scale is the central problem in ecology, unifying population biology and ecosystems science, and marrying basic and applied ecology. Applied challenges ... require the interfacing of phenomena that occur on very different scales of space, time, and ecological organization." (Levin 1992)

Scale usually/traditionally has been ignored for logistical ease until quite recently: "Kuhn’s concept of a paradigm shift is a useful way to interpret the [1988] annual meeting of the [Ecological Society of America]...Every symposium or session I attended featured, included, or was structured by the concept of scale...I left feeling I had observed one of those rare creatures of the intellectual bestiary, a paradigm shift." (Golley 1989)

Meentemeyer and Box (1987) call for a "science of scale" in which scale is explicitly examined in each study.

Components of scale: definitions -

Any discussion must begin by defining terms. Scale, in particular, has been plagued by imprecise and inconsistent usage of terms. Click here for some basic definitions.

Scale is a: -spatiotemporal window -range of perception

A clarification of terms: "Scale" as used in this class is not the same as "level of organization." Scale refers to the spatial domain of the study, whereas level of organization depends on the criteria used to define the system. For example, population-level studies are concerned with interactions among conspecific individuals, whereas ecosystem-level studies are concerned with interactions among biotic and abiotic components of some process such as nutrient cycling. One could conduct either a small- or large-scale study of either population- or ecosystem-level phenomena. There are 2 usages of the term "scale": colloquial (used in ecology) and cartographic, and these are opposites to one another! Colloquial – Cartographic –

Scale has of two components: grain and extent. Click here for some generalities about each of these components. Grain – Extent –

Some properties of scale -

-Grain and extent are inversely correlated, a result of logistical constraints in measurement. Nature itself, of course, has fine grain and large extent. In sampling we sacrifice fine grain for large extent, or reciprocally, narrow the extent of our data when we require fine grain. Click here for an example of the relationship between scale and predictability.

-What is heterogeneous at one scale may be homogeneous at another: therefore, all measures are scale-dependent, and selection of a particular grain and extent may affect your results and conclusions.

- Grain and extent set the upper and lower limits of data resolution; we cannot detect patterns finer than the grain or coarser than the extent. (Patterns below and above, respectively, appear homogeneous.) From an organism's point of view, grain and extent are defined in terms of the organism's perceptive ability.

Implications of scale:

1) The relationship between the physical environment and biota may change based on the scale of observation, and predictor variables may change. -due to space and time lags, indirect effects, and feedbacks into systems that may not be observable at larger scales -example: potential evapotranspiration (PET) at local and continental scales

2) The scale of measurement or observation will affect the statistical relationships (particularly the variance) of a variable. -implications of changing extent or grain

3) The way we can study systems differs with scale, since the characteristics of systems at fine scales differs from those at broad scales.

4) The scale of investigation affects the patterns found. i) relationship between Least Flycatchers (Empidonax minimus) and American Redstarts (Setophaga ruticilla) (Sherry and Holmes 1988) - ii) Howell et al. (2000) found that for midwestern birds, 29% of species were more strongly affected by local variables (litter depth, stem density, cover of forbs, % canopy cover) and 67% were more strongly affected by landscape variables (% forest cover, mean patch size, edge density). iii) see Fuisz and Moskat 1992 for an example with beetles iv) see Wiens 1989 for additional examples

Since pattern-process relationships are scale-dependent, what is the "correct" scale to use?

"[T]here is no single natural scale at which ecological phenomena should be studied; systems generally show characteristic variability on a range of spatial, temporal, and organizational scales...[However, the fact that] there is no single correct scale or level at which to describe a system does not mean that all scales serve equally well or that there are not scaling laws" (Levin 1992).

There are some statistical techniques that can be used to identify scales (e.g. patch sizes), such as semivariance analysis, autocorrelation analysis, multiple regression, etc. We will go over some of these in lab.

Scaling -

Scaling can have 2 meanings: -derivation of power-law relationships (see e.g. Brown and West 2000), such as allometric relationships -transfer of information across scales (see e.g. Schneider 1994)

We will use the 2nd definition in this class: changing scale (grain or extent) is scaling. An increase in grain usually decreases variance; an increase in extent usually increases variance. Changing scale can affect the conclusions drawn in a study. For example, Turner et al. (1989) found that changing grain can affect estimates of diversity, dominance, and contagion.

At what spatial scale has most ecological research been conducted? (click here and see Kareiva and Andersen 1988) And yet the results from these studies are often used to represent global-scale phenomena! It is true that ecological studies can seldom if ever be done at large enough spatial and temporal scales to encompass all of the possible influencing factors and to capture natural variation (for reasons of money, time, and the limited human lifespan [and attention span]). But how well can such smaller scales represent nature? There are certain ecologists who are convinced that extrapolation from small-scaled studies is futile (see e.g. Carpenter 1996–there are several subsequent replies and rebuttals to this paper).

Using your data to infer patterns at larger or smaller scales is extrapolation and interpolation, respectively. Because pattern-process relationships are seldom linear, however, extrapolation and interpolation are fraught with peril! Consequences of scaling -

Click here for an example of the effects of changing grain and extent.

As one changes scale (and see Table 1 in Wiens 1989): scaling relationships are usually not continuous. Krummel et al. (1987) example of domains of scale separated by transition zones: below 70 ha, landscape patterns were driven by individual landowners’ uses of their plots of land (e.g. for cropland, pasture, etc.). Above 70 ha, landscape patterns were driven by topography and presence of streams and rivers. Implication: mechanisms differ within and outside domains (often linear within and nonlinear outside).

What to do if you have data from multiple scales: As in the previous lecture where the importance of sample size was discussed, it is important to study pattern-process relationships at multiple scales. Data from multiple scales provide alternative and often complementary information. For example, Niemela et al. (1996) studied the abundance and diversity of forest arthropods at different scales (between-stand scale vs. within-stand microhabitat scale). He found that local-scale patterns were affected by regional-scale biogeographic processes (e.g. microhabitats were determined by type of forest stand), with some uniquely local details. The amount (proportion) of forest in the landscape affected diversity within the forest stands (e.g. landscapes with 10% forest differed from those with 90% forest). local vs. regional effects - review by Mazerolle and Villard 1999 vertebrates - invertebrates -

3 components to scale-dependency -

1) environmental scaling (structural) -

2) observational scaling (perceptual) - In German, the term "umwelt" is used to define the surrounding environment as perceived by a person or organism (distinction between perceived world and real world).

3) organism response (functional) - what Farina (2006) calls an "eco-field" perspective, whereby the spatial configuration of objects carries a meaning for a specific function for an organism; must take an organism-centered viewpoint and not a structure- or pattern-centered one e.g. effect of body size: With 1993 (Ph.D. dissertation, Colo. State U.) grasshoppers, body size, and vagility -

An animal's mobility affects its perception of landscape pattern. e.g. McIntyre 1997 - habitat selection (use vs. availability) in beetle Eleodes hispilabris at small scale (cm2) - E. hispilabris avoids shrubs at larger scale (km2) - E. hispilabris selectively occupies shrubby areas different mechanisms of habitat selection operating at different scales (obstacle avoidance vs. foraging)

Therefore, landscape structure (spatial pattern) must be defined in terms of scale, which ultimately relates to function (process).

References:

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