why study vegetation so closely? "since vegetation is the cornerstone of all biospheric...

Why study vegetation so closely?

"Since vegetation is the cornerstone of all biospheric development — all animals eat plants directly or indirectly — it's the fundamental measure of the Earth's habitability. So the most important thing our products can do is quantify whether global vegetation is declining in magnitude or vigor"

P. Running mid 80’s NASA

LANDSCAPE ECOLOGY

• combines the horizontal approach of geography in examining the spatial interplay of natural phenomena with the vertical approach of ecology in studying functional interplay

•Ecology is the scientific study of the interactions between organisms and their environment.

•Landscape ecology is a sub-discipline of ecology, focussing on spatial relationships and the interactions between patterns and processes.

Hotspots

Mt Cameroon DFID Project

Research Consortium Tempos -Temporal and Spatial Diversity of Boreal Forest and Peatland Vegetation

• Spatial Structure and Quality of the landscape

• Forest fragmentation

• Spatial pattering and dynamics of bird species

• Explain decreasing trend on breeding bird populations

» Metapopulation capacity » Habitat factors and constraints

Short term Goals

• How many patches of ‘suitable habitat’ type coexist within the landscape

• Explain ‘landscape level mechanisms’ to facilitate understanding of complex environments

• The Temporal framework will consider three points in time: Years 1987 - 1994 - 2000

Lammi study area

Russia

Study area

1000 km

FinlandNorway

Sweden

N

Patch Definition

• Patches are defined as regions that are more-or-less homogeneous with respect to a measured variable.

• There are different approaches for defining patches.

Patches can be characterized compositionally in terms of the variables measured within them. This may include the mean (mode, central, or max) value and internal heterogeneity (variance, range).

In spatial applications, we're often interested in more than these variables; we want additional information about the patch's shape or spatial configuration.

Patch CharacteristicsA patch can be described by its:

Area - the size of the patch, in units of map scale (e.g., m) or as a proportion of the total map area.

For some applications, area may be subdivided into edge versus interior (core) area, with edges defined in terms of some buffering distance.

Perimeter (Edge) - the lineal measure of circumference of a patch.

Shape complexity - often summarized in terms of edge/area ratio. In many instances, this ratio is normalized to take on a value of 1.0 for the most compact shape possible (a square for raster data; a circle, for polygons).

• Most patch-definition procedures (especially GIS's) provide these indices simply, even automatically. For example, virtually all GIS packages keep track of the area and perimeter (edge) of each patch (polygon) in a vector coverage.

Levels of Patchiness• While individual patches have relatively few attributes, collections of patches may

have a variety of aggregate properties.

Commonly, indices of patchiness may be defined at four levels: • Patch-level metrics are those defined for individual patches

• Class-level metrics are integrated over all the patches of a given type (class).

These may be integrated by simple averaging, or through some sort of weighted-

averaging scheme to bias the estimate to reflect the greater contribution of large

patches to the overall index. For example, FragStats (McGarigal and Marks 1995)

provides class-level metrics that are simple averages as well as averages weighted

by patch area.

• Regional metrics are aggregated over one or more classes within a specified

subregion of a landscape. This subregion may be specified as within a bounding

polygon, or as a window that is moved over the region to provide local estimates of

various metrics.

• Landscape-scale metrics are further integrated over all patch types or classes

over the extent of the data.

High Resolution View of Amazonia

• While all metrics at higher levels are derived from patch-level attributes, not all metrics are defined at all levels. In particular, collections of patches of various types have aggregate properties that are undefined (or trivial) at lower levels.

• The fact that most higher-level metrics are derived from the same patch-level attributes has the further implication that many of the metrics are correlated. Thus, they provide overlapping and perhaps redundant information .

Components of Pattern

There are two main components of landscape pattern (O'Neill et al. 1988):

• Composition

Composition refers to the variety and relative abundance of patch types represented on the landscape. This component of pattern is typically

summarized with diversity indices.

• Configuration or Structure Structure connotes the spatial arrangement, position, orientation, or shape

complexity of patches on the landscape. There are various indices of landscape structure.

Stand Age

• Stand age for the Lammi Region in Southern Finland

NumP

34499

4679843731

56115

30520

10000

20000

30000

40000

50000

60000

2-20 years 20-50 50-80 80-120 >120

Age group

Nu

mb

er

of

Patc

hes

NumP

Mean Patch size (ha)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

2-20 years 20-50 50-80 80-120 >120

Age group

Mean

Patc

h s

ize (

ha)

Mean Patch size (ha)

• Mean patch size and number of patches as indices of landscape configuration.

• These metrics differ with the heterogeneity of the landscape

Mean Patch Size (ha)

02468

10

Stand volume

MP

S (

ha

) Pine

Spruce

Birch

Broad_leaved

0

10000

20000

30000

40000

50000

60000

70000

80000

Pine

Spruce

Birch

Broad_leaved

mm• Black corresponds to Spruce coverage for the Lammi Region -

• Green areas show non-forest (mostly water bodies and agriculture)

• Point data show breeding sites for woodpecker

• Volume of Spruce for the Lammi Region -

• Pink colored areas show non-forest (mostly water bodies and agriculture)

• Point data show breeding sites for woodpecker

Core Area metrics

• All core area metrics are per disjunct cores

• Distance to calculate interior patch areas was 1 pixel size (i.e. 25m from the edge)

• Core area density is the relative number of disjunct core patches relative to the landscape area

Core Area

0

2500

5000

7500

10000

12500

15000

17500

20000

22500

25000

>2<=40 >40<=160 >160<=240 >240<=400

Volume

To

tal C

ore

are

a (

ha)

Pine

Spruce

Birch

Broad_leave

Core Area Density

0

5

10

15

20

25

30

>2<=40 >40<=160 >160<=240 >240<=400

Volume

Nu

mb

er

of

dis

jun

t co

re

are

as/

ha Pine

Spruce

Birch

Broad_leave

Scale Issue

‘One must recognize that the description of the system will vary with the choice of scales; that each species, including the human species, will sample and experience the environment on a unique range of scales; and that, rather than trying to determine the correct scale, we must understand how the system description changes across scales’

Levin 1992

Epilogue

Which aspect of pattern matters, of course, depends on the application. The choice of metrics should reflect explicitly some hypothesis about the observed landscape pattern and what processes or constraints might be responsible for that pattern.