2. What Is Ecology?
The word ECOLOGY was coined by Ernst
Haeckel in 1869. It is derived from the Greek
oikos, meaning "household", "home," or
"place to live" and logos, "the study of.“
Haeckel’s definition: "...the investigation of
the total relationships of the animal both to its
inorganic and its organic environment...“
3. What Is Ecology? Other definitions I:
"...scientific
natural history." (Elton 1927)
"...the scientific study of the distribution and
abundance of animals." (Andrewartha 1961)
"...the study of the structure and function of
nature" (Odum 1971)
"...the study of the adaptations of organisms
to their environment" (Emlen 1973)
"...the scientific study of the relationships
between organisms and their
environments" (McNaughton and Wolfe
1979)
4. What Is Ecology? Other definitions II:
"...the scientific study of the interactions that
determine the distribution and abundance of
organisms." (Krebs 1985)
"...the study of the principles which govern
temporal and spatial patterns for
assemblages of organisms" (Fenchel 1987)
"...the study of the relationships between
organisms and the totality of the physical and
biological factors affecting them or
influenced by them" (Pianka 1988)
5. Collectively, these definitions convey the
notion that:
Theenvironment influences organisms
AND, organisms influence the environment
The fact that we are breathing oxygen
(generated mostly by the process of
photosynthesis) is a rather striking example
of the power of organisms to influence the
environment
6. What do ecologists study?
How do ecologists study things?
Experimental papers
submitted to the
journal Ecology
between 1980-86
>50% of studies
used experimental
plots <1m in
diameter!
>95% used plots
<100m in diameter!
7. Themes in Landscape Ecology:
I. Scaling Issues
How do we scale up?
What is the most appropriate spatial
and temporal scale to use when
addressing a given question? (see
Urban et al. 1987 and others)
Butwait…..What do we mean by
“scale”
8. Scale: A confusing term
This term is used inconsistently throughout
the literature. You will need to learn to read
between the lines to determine how each
author intends to use this term.
The Turner et al. text (on reserve) (Table 1.1)
defines scale as the “spatial or temporal
dimension of an object or process,
characterized by both grain and extent.”
9. Scale: A confusing term
grain + extent ?
Extent: defined (Table 2.1) as “the size of the
study area or the duration of time under
consideration.” Note that this definition
includes both a spatial and temporal
component
Grain: a potentially confusing term. Defined
(Table 2.1) as “the finest level of spatial
resolution possible within a given data set.”
Be careful! Some authors treat grain and
scale as equivalent terms!
11. The formal definition of Map
scale is counter-intuitive!
Map Scale 1:100,000 1:100
Map ratio 1/100,000 = 1/100 = 0.01
0.000001
The way geographers & Small scale Large scale
cartographers describe (map ratio is (map ratio is
these maps. smaller!) larger!)
The way most people Large scale (only Small scale
would (incorrectly) large features (small features
describe these maps. visible! And visible! And
large extent.) small extent.)
A less confusing way to Coarse-scale or Fine-scale or
describe these maps coarse grained fine-grained
12. Scale: which definition?
You need to read between the lines to find out!
Scale: grain + extent? Maps with large
extent are usually coarse-grained; fine-
grained maps usually have small
extent.
Scale: grain only?
Large/small Scale: geographer’s
definition or common (incorrect)
definition?
13. Themes in Landscape Ecology:
II. The study of larger areas
Implicitin the focus on scaling issues is that
Landscape ecology deals with the study of
larger areas (landscapes) than has been the
case in “traditional ecology.”
How large is a landscape? No hard and fast
rules. “…a kilometers-wide mosaic over
which local ecosystems recur” (Forman
1995)
A more general definition that does not require
an absolute scale: “…..an area that is
spatially heterogeneous in at least one
factor of interest” (Turner et al. 2001; p. 7)
14. Themes in Landscape Ecology:
III. The real world is patchy
Patch: a surface area that differs from its
surrounding in nature or appearance (Table
1.1; and see other related terms in this table)
Patches can occur in space or time
Edge effects matter!
Traditionally, ecologists tried to ignore
edges. Sample sites located in the middle
of large uniform patches of vegetation.
15. Themes in Landscape Ecology:
IV. Analysis of connectivity in patchy
environments
How does the arrangement and
characteristic of patches influence
ecosystem processes?
Wildfire spread
Juvenile dispersal success
Seed dispersal success
Hydrologic response
16. Themes in Landscape Ecology:
V. Explicit consideration of the role of
humans
Role of humans often ignored when focused
on the study of 1m2 plots
The role of humans cannot be ignored at the
landscape scale (spatial domain)
The legacy of human land use can persist
for centuries to millennia (time domain)
17. Themes in Landscape Ecology:
VI. Interdisciplinary
Ecology, Biology, Computer Science, Geography,
Statistics, Aerospace Engineering (remote
sensing), Physics
For each paper you read this quarter, take a
moment to look at the mailing address of the
authors. What academic department are they
from? What agency? This gives you a hint about
the perspective they bring to any given analysis
18. Tools for Landscape Ecology:
I. Computers
fast, cheap computers …
and they keep getting faster
Processing speed closely
linked to transistor density.
This has been doubling
about every 18 months for
nearly 40 years (Moore’s
law)
Common desktop computers
capable of gigaFLOPS
Science 1996. 274:1834
19. Tools for Landscape Ecology:
II. Statistics
Shift from parametric statistics (t-test,
ANOVA, linear regression) to spatial
statistics
Geostatistic: exploiting spatial
autocorrelation
20. Tools for Landscape Ecology:
III. GIS and Remote Sensing
Made possible by improvements in computers
These tools have made it possible to work
effectively with large spatial data sets (maps).
Often used as tools to prepare datasets for use in
various models
GIS also often used to display and help analyze
output from these models.
21. Tools for Landscape Ecology:
IV. Landscape Metrics
As with many new fields of study, the early
years of landscape ecology (the 1980s)
focused on the development of tools to
describe landscape patterns
These metrics include, patch size, shape,
proximity, edge density, dominance,
diversity, fractal dimension, and many more
22. Tools for Landscape Ecology:
V. Models
These take many forms. We will expand on
this in a week or so.
23. Origins of Landscape Ecology:
The European School
German biogeographer, Carl Troll coined the term
landscape ecology in 1939
Emphasis on typology, classification,
nomenclature and mostly concerned with the
“built” (human) environment
In the U.S., this perspective is most often found in
Landscape Architecture, Planning or Design
schools rather than in Biology, Environmental
Science or Ecology programs
24. Origins of Landscape Ecology:
The American School
Also found in Australia and elsewhere, including
in Europe
Comparatively young; launched by a few meetings
in the early 1980s (Risser et al. 1984)
More focused on natural or semi-natural systems
Much more heavily invested in theory and models
Most practitioners are in Biology, Environmental
Science, Ecology, Natural Resources or
Geography programs or Natural Resources
Management Agencies
25. What is Landscape Ecology?
…..focuseson (1) the spatial relationships
among landscape elements, (2) the flows of
energy, mineral nutrients, and species
among the elements, and (3) the ecological
dynamics of the landscape mosaic through
time (Forman 1983)
26. What is Landscape Ecology?
….focuses explicitly upon spatial patterns.
Specifically, landscape ecology considers
the development and dynamics of spatial
heterogeneity, spatial and temporal
interactions and exchanges across
heterogeneous landscapes, influence of
spatial heterogeneity on biotic and abiotic
processes, and management of spatial
heterogeneity (Risser et al. 1984)
27. What is Landscape Ecology?
….is motivated by a need to understand the
development and dynamics of pattern in
ecological phenomena, the role of
disturbance in ecosystems, and
characteristic spatial and temporal scales of
ecological events (Urban et al. 1987)
28. What is Landscape Ecology?
….emphasizes broad spatial scales and the
ecological effects of the spatial patterning
of ecosystems (Turner 1989)
Notes de l'éditeur
To answer this question, let’s begin by asking another question; What is ecology? (last revision: 1/8/2003; minor updates 9/28/2004)
Above is a short list of definitions that have been suggested by any number of authors. Each of these definitions includes some feature that I like. I don’t want to get bogged down in these definitions but the words in bold give you give you some sense of what I feel should be included in a definition.
Peter Karieva is a professor at the university of Washington and for several years, he was the editor of Ecology ; this is the main American Journal in the field. During his tenure as editor (during the mid-1980s), just for kicks, he kept track of the characteristics of all experimental papers that were submitted for publication. These experimental papers, by definition, involved some sort of manipulation, this would exclude descriptive papers. This figure summarizes what he found ( figure 1 from Karieva and Anderson 1988) . You can see from this figure that the overwhelming majority of these papers were based on the study of experimental plots that were one meter or less in diameter!!!! This figure speaks volumes about the problems that scientists face today when we are asked to address real world problems! These are the data that we have to work with in our field today yet nearly all of the really interesting question that we face as scientist and as resource managers deal not with meter square plots, but with much larger scale features. Given that these are the only data we have to work with, how do we take these data and answer questions about the function of ecosystems, the management of large watersheds and National Forests???
Note that Table 1.1 in your book defines a number of terms that we will be using throughout the course. You should be sure that you understand all of these terms. All are fair game for the exam!
The role of humans in the time domain: legacies. The legacy of human activity must also be considered in the time domain. La Selva Biological Station (Costa Rica): soil chemistry different in undisturbed forest at site of a 2000 yr old village site. Africa: Masai home sites/corrals. Old-growth rainforest in Peru/Columbia-- long history of slash and burn
This makes it possible to use more sophisticated statistical tests, computationally intensive simulation models and take advantage of things like satellite data and GIS.
Parametric statistics (t-tests, ANOVA, regression) are very powerful and they’ve been around since the 1930s or so. Their power comes at a cost and that cost includes a very imposing set of assumptions. A key assumption is sample independence. The real world is full of spatial autocorrelation. Since traditional statistical techniques can ’ t deal with this correlation, you have to go to great lengths to eliminate it in your data collection procedures. In practice, what this means is that you make sure that your samples sites are far enough apart that you don ’ t have to worry about it. This works, but, wouldn’t it be nice if you could make this spatial correlation work for you? One of the things that we’d like to be able to do with our hard-won data is scale-up; we might want to take our data from those meter-square plots and project our results over a larger area to paint a map of some feature.........expand...... It turns out that gold miners figured out one approach to this a long time ago. ......expand....... Geostats
Parametric statistics (t-tests, ANOVA, regression) are very powerful and they’ve been around since the 1930s or so. Their power comes at a cost and that cost includes a very imposing set of assumptions. A key assumption is sample independence. The real world is full of spatial autocorrelation. Since traditional statistical techniques can ’ t deal with this correlation, you have to go to great lengths to eliminate it in your data collection procedures. In practice, what this means is that you make sure that your samples sites are far enough apart that you don ’ t have to worry about it. This works, but, wouldn’t it be nice if you could make this spatial correlation work for you? One of the things that we’d like to be able to do with our hard-won data is scale-up; we might want to take our data from those meter-square plots and project our results over a larger area to paint a map of some feature.........expand...... It turns out that gold miners figured out one approach to this a long time ago. ......expand....... Geostats
Parametric statistics (t-tests, ANOVA, regression) are very powerful and they’ve been around since the 1930s or so. Their power comes at a cost and that cost includes a very imposing set of assumptions. A key assumption is sample independence. The real world is full of spatial autocorrelation. Since traditional statistical techniques can ’ t deal with this correlation, you have to go to great lengths to eliminate it in your data collection procedures. In practice, what this means is that you make sure that your samples sites are far enough apart that you don ’ t have to worry about it. This works, but, wouldn’t it be nice if you could make this spatial correlation work for you? One of the things that we’d like to be able to do with our hard-won data is scale-up; we might want to take our data from those meter-square plots and project our results over a larger area to paint a map of some feature.........expand...... It turns out that gold miners figured out one approach to this a long time ago. ......expand....... Geostats
Parametric statistics (t-tests, ANOVA, regression) are very powerful and they’ve been around since the 1930s or so. Their power comes at a cost and that cost includes a very imposing set of assumptions. A key assumption is sample independence. The real world is full of spatial autocorrelation. Since traditional statistical techniques can ’ t deal with this correlation, you have to go to great lengths to eliminate it in your data collection procedures. In practice, what this means is that you make sure that your samples sites are far enough apart that you don ’ t have to worry about it. This works, but, wouldn’t it be nice if you could make this spatial correlation work for you? One of the things that we’d like to be able to do with our hard-won data is scale-up; we might want to take our data from those meter-square plots and project our results over a larger area to paint a map of some feature.........expand...... It turns out that gold miners figured out one approach to this a long time ago. ......expand....... Geostats
Emphasis on the effects of pattern on process rather than process on pattern