Emergence of Landscape Ecology

Emergence of Landscape Ecology

Equilibrium View

• Constant species composition

• Disturbance & succession = subordinate factors

• Ecosystems self-contained• Internal dynamics shape

trajectory• No need to look outside

boundaries to understand ecosystem dynamics

Structure

Function

?

?

?

?

Emergence of Landscape Ecology

Dynamic View

• Disturbance & ecosystem response = key factors

• Disturbance counter equilibrium

• Ecosystems NOT self-contained

• Multiple scales of processes, outside & inside

• Essential to examine spatial & temporal context

Structure

Function

Scale• What’s the big deal?

• Seminal pubs– Allen & Starr (1982) – Hierarchy: perspectives

for ecological complexity– Delcourt et al. (1983) – Quaternary Science

Review 1:153-175– O’Neill et al. (1986) – A hierarchical concept

of ecosystems

Ecological Scaling: Scale & Pattern

• Acts in the “ecological theatre (Hutchinson 1965) are played out across various scales of space & time

• To understand these dramas, one must select the appropriate scale

Tem

pora

l Sca

le

Spatial ScaleFine

Sho

rt

Coarse

Lon

g

Recruitment

Treefalls

Windthrow

Secondary Succession

Species Migrations

SpeciationExtinction

Fire

Ecological Scaling: Scale & Pattern• Different patterns emerge, depending

on the scale of investigation

Am

eric

an R

edst

art

Least Flycatcher

Am

eric

an R

edst

art

Least Flycatcher

Local Scale(4 ha plots)

Regional Scale(thousands of ha)

Ecological Scaling: Components of Scale

• Grain: minimum resolution of the data– Cell size (raster data)

– Min. polygon size (vector data)

• Extent: scope or domain of the data– Size of landscape or

study area

Ecological Scale

• Scale characterized by:– grain: smallest

spatial resolution of data

e.g., grid cell size, pixel size, quadrat size (resolution)

Fine Coarse

Ecological Scale

• Scale characterized by:– extent: size of

overall study area (scope or domain of the data)

Small Large

Ecological Scaling: Components of Scale

• Minimum Patch Size: min. size considered > resolution of data (defined by grain)– Size of landscape or study

area

Ecological Scaling: Definitions• Ecological scale & cartographic scale are exactly opposite

– Ecological scale = size (extent) of landscape

– Cartographic scale = ratio of map to real distance

Scale in Ecology & Geography

• ecological vs. cartographic scale

Ecology Geography

Small

(Fine)

Fine resolution

Small Extent

Coarse resolution

Large Extent

Large

(Broad)

Coarse resolution

Large extent

Fine resolution

Small extent

Scale in Ecology & Geography

• ecological vs. cartographic scale– e.g., map scale

1:24,000 vs. 1:3,000fine vs. coarselarge vs. small extent

1:24,000

1:200,000

Ecological Scaling: Components of Scale

• Grain and extent are correlated

• Information content often correlated with grain

• Grain and extent set lower and upper limits of resolution in the data, respectively.

Ecological Scaling: Components of Scale

• From an organism-centered perspective, grain and extent may be defined as the degree of acuity of a stationary organism with respect to short- and long-range perceptual ability

Ecological Scaling: Components of Scale

• Grain = finest component of environment that can be differentiated up close

• Extent = range at which a relevant object can be distinguished from a fixed vantage point

Fine CoarseScale

ExtentGrain

Ecological Scaling: Components of Scale• From an anthropocentric

perspective, grain and extent may be defined on the basis of management objectives

• Grain = finest unit of mgt (e.g., stand)

• Extent = total area under management (e.g., forest)

Ecological Scaling: Components of Scale• In practice, grain and extent often dictated by scale of

available spatial data (e.g., imagery), logistics, or technical capabilities

Ecological Scaling: Components of Scale• Critical that grain and extent be defined for a study and

represent ecological phenomenon or organism studied.• Otherwise, patterns detected have little meaning and/or

conclusions could be wrong

Scale: Jargon• scale vs. level of organization

Space - Time

Space - Time

Space - Time

Individual

Population

Community

Ecological Scaling: Implications of Scale• As one changes scale, statistical relationships may

change:– Magnitude or sign of correlations– Importance of variables– Variance relationships

Implications of Changes in Scale

• Processes and/or patterns may change• Hierarchy theory = structural

understanding of scale-dependent phenomena

ExampleAbundance of forest insects sampled at different distance Intervals in leaf litter,

Implications of Changes in Scale

0

5

10

15

20

25

30

35

40

45

PredatorPrey

Insects sampled at 10-m intervals for 100 m

Implications of Changes in Scale

0

5

10

15

20

25

30

35

40

45

PredatorPrey

Insects sampled at 2000-m intervals for 20,000 m

Identifying the “Right” Scale(s)

• No clear algorithm for defining

• Autocorrelation & Independence • Life history correlates

• Dependent on objectives and organisms

• Multiscale analysis!

• e.g., Australian leadbeater’s possum

Multiscale Analysis

• Species-specific perception of landscape features : scale-dependent

– e.g., mesopredators in Indiana

• Modeling species distributions in fragmented landscapes

Hierarchy Theory

• Lower levels provide mechanistic explanations

• Higher levels provide constraints

Scale & Hierarchy Theory

• Hierarchical structure of systems = helps us explain phenomena

–Why? : next lower level

–So What? : next higher level

• minimum 3 hierarchical levels needed

Constraints (significance)

Level of Focus (level of interest)

Components (explanation)

Constraints

Why are long-tailed weasel populations declining in fragmented landscapes?

Components

Population

Community

Individual

Constraints

Why are long-tailed weasel populations declining

in fragmented landscapes?

Small body sizemobility

Population

Community

Individual

PredatorsCompetitorsPrey dist’n

Why are long-tailed weasel populations declining

in fragmented landscapes?

Components

Population

Community

Individual

Scale & Hierarchy Theory • Change scale:

1) influential variables might not change, but

2) shift in relative importance likely

Example: Predicting rate of decomposition of plant matter

Local scale = lignin content & environ. variability

Global scale = temperature & precip.