Direct gradient analysis (continued)

Lecture graphics

Characteristics of DGA:

Data are plotted along environmental axes which are generally accepted as given. Axes can be:

direct

indirect

synthetic

Species, communities, and community-level characteristics can be plotted

Several dimensions are possible

Some form of data-smoothing is usually employed prior to presentation

common smoothing technique is weighted average for each datum; e.g.,

{current datum_smoothed = previous datum + 2 × current datum + next datum/4}

resulting curve is less "noisy" than original data

Whittaker offered the following conclusions about DGA:

1. The general form for the distribution of a species population along an environmental complex-gradient is the bell-shaped curve
   • The center (or mode) of a species population along a complex-gradient is not at its physiological optimum but is a center of maximum population success in competition with other species populations

   • The centers of species populations are scattered along a complex-gradient in an apparently random manner

   One important qualification: in some cases, competing species appear to be not randomly but regularly distributed along environmental complex-gradients

   According to Whittaker, these considerations imply the following:

2. Species do not form well-defined groups of associates with similar distributions, clearly separate from other such defined groups, but are distributed according to the principle of species individuality; each species is distributed in its own manner, according to its own genetic, physiological, and population response to environmental factors that affect it, including effects of other species

3. Along an environmental complex-gradient, species populations (w/ their scattered centers and broadly overlapping distributions) form a population continuum or compositional gradient, suggesting that, in the absence of environmental discontinuity or disturbance, communities intergrade or are continuous w/ one another

4. These conclusions led Whittaker to reject the "community- unit" hypothesis

Whittaker's conclusions were strongly influenced by his belief in bell-shaped curves of species distributions

The bell-shaped curve concept was challenged by Austin (1976, Vegetatio 33:33-41) in a summary of previously published data:

	linear	bell	symmetric	skewed	very skewed	bimodal	total
Curtis	4	0	3	7	2	8	24
Noy-Meir	0	1	2	4	0	0	7
Monk	3	2	3	1	1	8	18
Total	7	3	8	12	3	16	49
Percent of Total	14	6	16	24	6	33

	bell (%)	skewed	shouldered	plateau	bimodal	total
Whittaker
Smokies	8 (23%)	6	10	2	9	35
Siskiyous	14 (27%)	16	8	1	12	51

Austin therefore concluded that the general form of the species population is not normal, bell-shaped. And he was considering data which had already been smoothed

Werger (1983, Vegetatio 52:141-150) used a very conservative yardstick for "normal" distribution (50% of variation accounted for by curve)

31% of species normally distributed:

1 of 8 species (12%) on ridge tops

12 of 22 species (55%) midslope

5 of 32 species (16%) in swales

The data collected and summarized by Austin and Werger indicate that there is no a priori reason to assume bell-shaped normal curves for distributions of species on gradients

Conclusions about DGA:

1. DGA is of unquestionable value and utility in ecology as a means of
   • data summarization and presentation, and

   • hypothesis generation

2. DGA is soundly based in classical plant ecology (e.g., Jack Major's functional factorial approach to plant ecology-- vegetation = f(topography, organisms, time, soil, climate)

3. The use of data-smoothing may be misleading

4. There is a high degree of subjectivity inherent in this method

5. DGA (esp. w/ "synthetic" indices) is inherently circular

   Circularity results from subjective (pre-conceived) sampling design--note that this was a criticism launched by Whittaker (among others) against the Clementsian approach of "seeing" communities and sampling w/in them.

   The DGA-based conclusion of vegetation continuum results from arbitrary, subjective sampling (just as the discrete-community conclusion derives from sampling w/in well-defined communities which appear to be different.

   Both schools describe, but do not answer "why"? Both groups base conclusions on descriptive data, w/o testing hypotheses.