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Community Theory. Kenneth M. Klemow, Ph.D. Wilkes University. www.fws.gov/arizonaes. “Pre-modern” community concept. Communities static entities Composition depended on: Climate Temperature Rainfall Soils Disturbance. Dynamic concept. Result of work by H. Cowles

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Community theory l.jpg

Community Theory

Kenneth M. Klemow, Ph.D.

Wilkes University


Pre modern community concept l.jpg

www.fws.gov/arizonaes

“Pre-modern” community concept

  • Communities static entities

  • Composition depended on:

    • Climate

      • Temperature

      • Rainfall

    • Soils

    • Disturbance


Dynamic concept l.jpg
Dynamic concept

  • Result of work by H. Cowles

  • Communities change over time

    • Parameters include

      • Species composition

      • Relative density

    • Due to internal processes

www.oceanservice.noaa.gov


Clementsian community concept l.jpg

www.nceas.ucsb.edu

www.tarleton.edu

Clementsian Community Concept

  • Introduced by Frederic Clements

  • Dominated ecological thinking in first 40 years of 20th Century

  • Key concepts

    • Association

    • Super-organismal analogy

    • Succession with seres, converging to monoclimax.


Association l.jpg

www.bigsurlandtrust.org

Association

  • Group of coevolved species.

  • Characteristic of climate

  • Extends for many square miles

  • Characteristic species composition

  • Can be classified

  • Equated to super-organism

  • Adjoining communities interface at ecotone.


Succession l.jpg

www.nescb.org

www.tarleton.edu

Succession

  • Deterministic, orderly change of species composition on a site.

  • Can be classified into

    • Primary

    • Secondary

  • Can be classified into

    • Hydrarch

    • Mesarch

    • Xerarch

  • Consists of a series of “seral” stages.

  • Relay floristics.

  • Converge to monoclimax characteristic of area.

  • Equated to ontogenetic development in organism



Individualistic dissent l.jpg

www.botany.org

Individualistic dissent

  • Proposed by Henry Gleason in 1920s and 1930s.

  • Communities not highly coevolved aggregations of species

  • Instead, chance assemblages of species having overlapping tolerances for prevailing environment.

  • Rejected deterministic, superorganismal analogy

  • Species change along gradients by blending continuum

  • Tight ecotones may occur when environmental change abrupt, but not necessarily true.



Evaluating clements vs gleason l.jpg

www.nceas.ucsb.edu

www.botany.org

Evaluating Clements vs Gleason


Robert h whittaker l.jpg

oz.plymouth.edu

Robert H. Whittaker

  • Ph.D University of Illinois.

  • Conducted analysis of woody plants

  • Computed importance values for each species

  • Related to obvious environmental gradient

    • Smoky Mountains, TN

    • Siskyou Mountains, Oregon

    • Santa Catalina Mountains, Arizona.



Whittaker s findings13 l.jpg

Siskyou Mountains, Oregon

Santa Catalina Mountains, Arizona.

home.messiah.edu

Whittaker’s findings


What if an overriding gradient is not evident l.jpg
What if an overriding gradient is not evident?

  • Perform an indirect gradient analysis through ordination or other statistical technique

  • Main steps:

    • Calculate Importance Values for each species in each community

    • Determine Coefficient of Community (CC) for each pair of communities


Determining coefficient of community cc l.jpg
Determining Coefficient of Community (CC)

  • CC =  min IV

    • Where min IV is lower Importance Value for each species




Determine community pair with highest di l.jpg
Determine community pair with highest DI

  • These become endpoints of axis.

C1

C3

20

40

60

80

100

0


Place other communities at euclidean distance from reference l.jpg
Place other communities at Euclidean distance from reference

  • C4 is 70 from C1, 50 from C3

C4

50

70

C1

C3

20

40

60

80

100

0


Place other communities at euclidean distance from reference20 l.jpg
Place other communities at Euclidean distance from reference

  • C4 is 70 from C1, 50 from C3

  • Drop perpendicular

50

70

C1

C4

C3

20

40

60

80

100

0


Where would c2 go l.jpg
Where would C2 go?

C1

C4

C3

20

40

60

80

100

0


Where would c2 go22 l.jpg
Where would C2 go?

C2

60

40

C1

C4

C3

20

40

60

80

100

0


Where would c2 go23 l.jpg
Where would C2 go?

60

40

C1

C2

C4

C3

20

40

60

80

100

0


Now plot iv values for each species against community positions l.jpg

IV

20

40

60

80

100

0

C3

C1

C2

C4

Now plot IV values for each species against community positions


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