Plant Community Ecology Test #2

Front 1

mosaic diagram

Back 1

A measure of landscape complexity due to variation in species richness among communities and variation in commonness and rarity among species within a region.

R H Whittaker

Front 2

dimension reduction

Back 2

Process of collapsing highly multivariate data into a small number of dimensions.


Goals:
-Reduce the N-dimensions to fewer
-Retain as much information as possible
-Limit the distortions that canfound interpretation
-Maximize the relationship between a derived dimension and the underlying control

Front 3

Monte Carlo Methods

Back 3

Used to determine overall significance

Front 4

eigenvalue

Back 4

Number that, when used to multiply a population vector, gives the same result as multiplication by the transition matrix.


Contribution of each axis to total variation

Front 5

agglomerative/divisive classification

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Agglomerative: starts with all different and goes until all are in one group.

Divisive: assumes all same, then divides down to some criterion. (preferred, but few and far between)

Front 6

dendrogram

Back 6

Indicates degree of relationships among the entities.

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Front 7

non-hierarchical classification

Back 7

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Front 8

indicator species (in
general and in classification)

Back 8

A species used to place a community in a predetermined group.


May be single species, spectrum of species or growth forms (spectra)

Determined from:

-ordinations
-classifications
-natural history observations
-experiments
-literature

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species (inverse) ordination

Back 9

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Front 10

Competitive Exclusion

Back 10

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Front 11

Mass Effect

Back 11

The continuing rescue of species not really adapted to a site

Species go extinct except that there is continual replenishment from surroundings.

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Ecological niche

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Front 13

Niche differentiation

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Species shift their requirements to reduce impact (evolutionary impact) due to competitive pressures.

-Temporal avoidance
-Morphological avoidance (e.g. roots)
-Different shade requirements
-Limited by different factors

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Species area curve

Back 14

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Front 15

Allelopathy (direct interferece)

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The ways plants intereact with their surroundings.

Front 16

Competition (exploitation)

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The negative effects which one organism has upon another by consuming or controlling access to a resource that is limited in availability

Front 17

inter- and intraspecific competition

Back 17

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Front 18

Diffuse Competition

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Target may be impacted in proportion to the biomass of associates cumulative effects of neighbors of all species

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Predominant competition

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One species is main contributor to intensity

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symmetric competition/asymmetric
competition

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Species affect each other equally (symmetric)

vs

One species affects the other to a significantly greater degree.

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safe-site

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Less harsh islands in a stressful sea.


Microsite that satisfies germination requirements; number of available safe-sites may limit competition among adults.

Front 22

Preemption/tolerance/efficiency

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latent factors

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Control of vegetation may be layered, dispersal may control establishment, remove the dispersal limits and competition may control establishment, remove the competition and grazing may control establishment, remove grasing and seed predation may control establishment...Can be a problem in restoration.

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Mechanisms of succession

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facilitation

Back 25

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tolerance inhibition

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phrases that describe the
Clementsian view of succession

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nudation

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migration

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Movement of organisms or propagules.

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ecesis (establishment)

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reaction (facilitation)

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facilitation: Positive interaction among plants; a process by which early successional species increase the survival of later successional species; improvements; physical and biotic

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Approaches to study competition

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Front 33

chronosequence

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A set of communities of different ages since disturbance, assumed to represent a single community over time; Assume changes in space represent different successional age

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Toposequence

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Vegetation change over space assumed to be same as over time

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Priority effect

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Alternative stable states

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Trajectory

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Soil Chroma

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Intensity

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Paulustrine vs. Lacustrine

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Stabilization (climax)

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Hypothetical equilibrium end point of a successional sequences.

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Permanent Plots

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Front 42

Classification

Back 42

Process of forming groups of similar entities based on attributes using some rational, objective method.

Front 43

What are the main purposes of classification? List several reasons to do a classification, even if you believe your data represent continuous variation.

Back 43

-To summarize large, complex sets of data to produce mapping units; reduce data to manageable levels; help interpret environmental factors; test community hypotheses; refine models of community structure; assist experimental design; Different results from alternative methods can reveal unsuspected aspects of data; same results from different analyses give credence to real discontinuities in the data.

Front 44

List five subjective aspects of doing a classification.

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-Alternative methods produce alternative results
-Different observers may reach different conclusions
-Different subset of data migh lead to different classification.
-Transformations may emphasize dominance or rare sp.
-Editing rare specie can make groups more homogenous, or can obscure real differences among samples.

Front 45

CCA

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Differs from other methods by incorporating correlation and regressions between floristic data and environmental data by imposing further restrictions on community ordinations axes derived from CA based on the environmental data. Both quantitative and nominal data can be used together.

Ignores community structure--should be complimentary w/indirect ordination.

Starburst

Two matrices: species by sample, factor by sample.

Should be used

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Constrained ordination

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Used in CCA

Uses multiple linear regressions to select the best linear combinations of environmental variables.

Best: taken together, they explain the most variation in the species scores on each axis.

Front 47

Total variance in species data (inertia)

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In CCA, total information in the species data that could be "explained" that is associated with a environmental variable.

Front 48

Canonical coefficients

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In CCA, are regression coefficients derived from the iterative method. Have larger variances so can't sue standard significance tests. Represent contribution of variable to regression solution.

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R squared value

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In CCA, value for an exis provides an estimate of how well the variables "predict" the location of a sample.

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Constancy of each species

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the number of releves within which the species occurs.

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Differential species

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those that tend to occur together in associations

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Character species

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those that permit an association to be recognized.

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Fidelity

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measures the degree to which a species occurs in one and only one association

Front 54

TWINSPAN

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Uses all the information available at any given step.

Early mistakes carry through analysis.