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Title: 2.5 Investigating Ecosystems


1
2.5 Investigating Ecosystems
2
  • Review Zonation and Succession on your notes

3
Monitoring Abiotic Factors
  • Ecosystems can be roughly divided into-
  • Marine
  • Freshwater and
  • Terrestrial systems

4
Monitoring Abiotic Factors
  • Complete the diagram in your notes

5
MONITORING BIOTIC (LIVING) FACTORS
  • Once the abiotic conditions within an
    environmental gradient have been measured, we can
    begin to ask questions about the distribution of
    organisms within the study area
  • Which species are present
  • The size of a particular population of organisms
  • The productivity in a particular area
  • The diversity of a particular area

6
MONITORING BIOTIC (LIVING) FACTORS
  • Complete the table in your notes

7
COLLECTING DATA - Where?
  • When collecting environmental data, it is almost
    impossible to collect every possible data point
  • We use sampling methods to make estimations
  • These methods enable us to get a random sample
    from an entire ecosystem and then use
    extrapolation to make estimates and predictions
  • In order to avoid bias it is important that these
    methods are truly random.
  • Two methods used in ecology to determine where to
    collect a sample are quadrats and transects.

8
Assumptions Made When Sampling
  • The sample is representative of the whole system
  • It is necessary to take enough samples so that an
    accurate representation is obtained
  • It is important to avoid bias when sampling

9
Estimating Populations of Organisms
  • We estimate populations because it would take way
    too long to count every living thing in a given
    ecosystem.
  • We can estimate populations of plants or animals
  • Random Sampling All organisms must have an equal
    chance of being captured.

10
Common Sampling Methods
  • Abundance of Non-motile Organisms
  • Transects and Quadrants
  • Abundance of Motile Organism
  • Actual Count (very difficult if large system)
  • Lincoln Index
  • Capture Mark - Recapture
  • Species Diversity
  • Simpson Diversity Index
  • For comparing 2 habitats or the change in one
    habitat over time

11
Lincoln Index
12
Measuring abundance of Mobile Organisms
  • If the organism is mobile we use a method called
    the capture-mark-recapture method
  • We then use this data to calculate the Lincoln
    Index

13
How to Capture Motile Organisms
  • REMEMBER IB Animal Experimentation Policy
  • Pitfall Traps
  • Small Mammal Traps
  • Tullgren Funnels (invertebrates)
  • Kick Net

14
Estimating Populations of Animals
  • Lincoln index (capture-mark-release-recapture)
  • n1 x n2
  • N n3
  • N Total number of population
  • n1 Number of animals first (mark all of them)
  • n2 Number of animals captured in second sample
  • n3 Number of marked animals in second sample
  • Ex. 40 mice were caught, marked (tail tattoo) and
    released. Later, 10 mice were recaptured, 4 of
    which had tattoo marks.

15
Lincoln Index
16
Example
  • 50 snowshoe hares are captured in box traps,
    marked with ear tags and released. Two weeks
    later, 100 hares are captured and checked for ear
    tags. If 10 hares in the second catch are
    already marked (10), provide an estimate of N
  • Realize for accuracy that you would recapture
    multiple times and take an average

17
Lincoln Index Assumptions
  1. The marked animals are not affected (neither in
    behavior nor life expectancy).
  2. The marked animals are completely mixed in the
    population.
  3. The probability of capturing a marked animal is
    the same as that of capturing any member of the
    population.
  4. Sampling time intervals must be small in relation
    to the total time of experiment of organisms life
    span.
  5. The population is closed (no immigration and
    emigration)
  6. No births or deaths in the period between
    sampling.

18
Some Possible Sources of Error
  • Emigration Immigration
  • Natural disaster or disturbance between captures
  • Trap happy or trap shy individuals
  • Organisms did not have enough time to disperse
    back into ecosystem
  • Animals lost marks between recapture

19
Quadrat Sampling
20
Estimating Populations of Plants
  • Quadrat Estimation
  • Population Density- The
  • number of plants within the
  • given area of the quadrat (m2)
  • Percentage Coverage-
  • How much of the area of a
  • quadrat is covered by plants?
  • Frequency- How often does a plant occur in each
    quadrat?
  • Acacia senegalensis was present in 47 of 92
    quadrats, for a frequency of 51

21
Square Quadrat Method
  • N (Mean per quadrat) (total area)
    Area of each quadrat
  • This estimates the population size in an area
  • Ex. If you count an average of 10 live oak trees
    per square hectare in a given area, and there are
    100 square hectares in your area, then
  • N (10 X 100 hectare2) / 1 hectare2 1000
    trees in the 100 hectare2

22
In addition to population size we can measure
  • Density of individuals per unit area
  • Good measure of overall numbers
  • Frequency the proportion of quadrats sampled
    that contain your species
  • Assessment of patchiness of distribution
  • Cover space within the quadrat occupied by
    each species
  • Distinguishes the larger and smaller species

23
Grid Quadrate
  • Measures percent frequency the of quadrats in
    which the species is found
  • OR
  • Measures percent coverage the of area within
    a quadrat covered by a single species
  • NOTE When you are looking at one species at a
    time
  • If not using a 10 x 10, you must turn into a
    percentage (squares covered/total of squares)

24
Percent Frequency
  •  

25
http//www.slideshare.net/nirmalajosephine1/biolog
y-form-4-chapter-8-dynamic-ecosystem-part-3-428394
37
26
Percent Coverage
1 m
  • Find the percent coverage
  • Count full squares
  • Now combine pieces to make full squares
  • Calculate percentage coverage
  • Percent Coverage

18
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27
Calculate Population Density
What is the population density of species x
? What is the population density of species
Y? What is the population density of species Z?
Quadrat 1 0.5m2
X X X W W
W X X W X
W X X X X
W X W X W
W z W W Y
28
Calculate Percentage Coverage
What is the percentage of plant coverage in this
quadrat?
Quadrat 1 0.5m2
X X W
W X X W X
W X X X
W X W
X W Y
29
Percentage Frequency
Quadrat 1
What is the frequency of species X? What about
species V?
X X X W W
W X X W X
W X X X X
W X V X W
W Z W W Y
Quadrat 2
Quadrat 3
X X X W W
W X X W X
W X X X X
W X W X W
W Z W W Y
Z Z Z W W
W Z Z Z Z
W Z Z W Z
W X W Z W
W Z W W Y
30
How choose quadrat size?
  • Think about the size of the organism.
  • Think about the area of the system.
  • The smaller the quadrat the more accurate,
    however the smaller the sample size
  • Larger quadrats increase inaccuracy but allow for
    broader sample of an area

31
Measuring Biomass
  • Get a sample of the organisms, dry them out
    completely in a dehydrating oven (to remove all
    water!), find the mass and extrapolate
  • If you collect 10 plants, dry them out and find
    their average dry biomass to be 20g, what would
    the biomass of a population of 2500 plants be?
  • 50,000g
  • Remember biomass can be used to create pyramids
    of biomass when looking at energy transfers and
    is needed for many productivity calculations!

32
Transets
33
Transects
  • A TRANSECT - A line, strip or profile of
    vegetation which has been selected for study.
    measure any of these abiotic and/or biotic
    components of an ecosystem along an environmental
    gradient

34
Transect
  • In order to complete a transect, a piece of
    string or measuring tape is laid out along the
    selected gradient.

35
Line Transects
  • A measured line is randomly placed across the
    area in the direction of an environmental
    gradient
  • All species touching the line are recorded along
    the whole length of the line or at specific
    points along the line
  • Measures presence or absence of species

36
Belt Transects
  • Transect line is laid out and a quadrant is
    placed at each survey interval
  • Samples are identified and abundance is estimated
  • Slow moving animals (limpets, barnacles, snails)
    are collected, identified then released
  • For plants an percent coverage is estimated

37
Belt Transects
  • Data collection should be completed by one
    individual as estimates can vary person to person

38
Transect
  • These can either be sampled continuously or as an
    interrupted transect where samples are taken at
    regular, fixed distances along the line.

39
Transect
  • To measure changes in space i.e. zonation, this
    technique should be completed within a short
    space of time to avoid any daily cycles
  • For studies of long term change i.e. succession,
    the transect should be repeated at the same time
    of day and at regular intervals over a suitable
    time period depending on what is being studied
    or assessed.

40
Kite Diagrams
  • Used to illustrate changes in species over space
    or time along an environmental gradient.
  • The width of each kite represents the
    percentage cover or abundance of that species.

41
Simpson Index
42
Species Diversity
  • The two main factors taken into account when
    measuring species diversity
  • 1. Richness
  • A measure of the number of different species
    present in a particular area.
  • The more species present in a sample, the
    'richer' the sample.
  • Takes no account of the number of individuals of
    each species present. It gives as much weight to
    those species which have very few individuals as
    to those which have many individuals.

http//www.countrysideinfo.co.uk/simpsons.htm
43
Species Diversity
  • The two main factors taken into account when
    measuring species diversity
  • 2. Relative Abundance
  • The relative number of individuals of each
    species present

http//www.countrysideinfo.co.uk/simpsons.htm
44
How Can We Know Diversity?
  • Use the Simpsons diversity index below

D ____________N (N-1)_______________
n1(n1-1) n2(n2 -1) n3(n3 -1) nk(nk -1) D
Diversity N Total number of organisms of all
species n number of individuals of a particular
species The higher the D value the more
diverse the sample is!!!!!
45
Example Data Calculations
  Abundance of Organism Abundance of Organism
  Ecosystem A Ecosystem B
species 1 3 5
species 2 7 4
species 3 26 12
species 4 9 7
species 5 7 0
Diversity 3.27
46
How can changes in these populations be measured?
  • Necessary because populations may change over
    time through processes like succession
  • But also because human activities may impact a
    population and we want to know how
  • Impacts include ? toxins from mining,
    landfills, eutrophication, effluent, oil spills,
    overexploitation

47
Analyzing Simpsons Index
  • Used to compare 2 different ecosystems or to
    monitor an ecosystem over time
  • D values have no units and are used as comparison
    to each other
  • High D Value Indicates
  • Stable and ancient site
  • More diversity
  • Healthy habitat
  • Low D Value Indicates
  • Dominance by one species
  • Environmental stress
  • Pollution, colonization, agriculture

48
How to Capture Motile Organisms
  • REMEMBER IB Animal Experimentation Policy
  • Pitfall Traps
  • Small Mammal Traps
  • Tullgren Funnels (invertebrates)
  • Kick Net

49
Classification
50
What is classification?
  • Science of grouping organisms based on their
    physical characteristics.

51
What characteristics do we use?
  • Structures (morphology)
  • Functions (physiology)
  • Biochemistry
  • Genetics

52
Why do we classify?
  • Identify organisms
  • Compare organisms
  • Identify relationships among organisms
  • Communicate with others (universal language)
  • Identify evolutionary relationships

53
Why do we classify?
  • What am I?
  • Firefly
  • Lightning bug
  • Glow Fly
  • Blinkie
  • Golden Sparkler
  • Moon bug
  • Glühwürmchen
  • Luciérnaga
  • Luciole
  • We all have different names for the same
    organismthis is a problem for communication.

54
From Aristotle to Linneaus
  • Aristotle (Greek philosopher)
  • (384-322 B.C)
  • First System of Classification
  • 1. Plants
  • Based on stem type
  • 2. Animals
  • Land, air or water

55
From Aristotle to Linneaus
  • Carolus Linneaus (Sweedish botanist)
  • (1707-1778)
  • Came up with modern classification system
  • Used binomial nomenclature (2 word naming system)
  • This two word name is called a scientific name
  • Composed of the genus name followed by the
    species name

56
Scientific Names
  • Either written in italics or underlined
  • Genus is always capitalized and species is always
    lowercase
  • Based on Latin
  • Examples
  • Cat Felix domesticus
  • Mosquito Colex pipens
  • Human Homo sapien

57
Funny Scientific Names
  • Agra vation (a beetle)
  • Colon rectum (another beetle)
  • Ba humbugi (a snail)
  • Aha ha ( a wasp)
  • Lalapa lusa (a wasp)
  • Leonardo davinci (a moth)
  • Abra cadabra (a clam)
  • Gelae baen, Gelae belae, Gelae donut, Gelae fish,
    and Gelae rol (all types of fungus beetles)
  • Villa manillae, Pieza kake and Reissa roni  (bee
    flies)

58
Dichotomous Keys
  • A series of yes/no questions about an organisms
    structure
  • Used to identify new and unknown organisms

59
Step 1 Identify the organism
  • Use dichotomous keys, field guides, observe a
    museum collection, or consult an expert
  • http//www.earthlife.net/insects/orders-key.htmlk
    ey
  • Sample key for insect ID
  • http//people.virginia.edu/sos-iwla/Stream-Study/
    Key/Key1.HTML
  • Macroinvertebrate key

60
Example of Dichotomous Key
  • 1a. Hair Present..Class Mammalia
  • 1b. Hair AbsentGo to statement 2

61
Example of Dichotomous Key
  • 2a. Feathers present..Class Aves
  • 2b. Feathers absent.Go to statement 3
  • 3a. Jaw Present..Go to statement 4
  • 3b. Jaw AbsentClass Agnatha

62
Example of Dichotomous Key
  • 4a. Paired fins presentGo to 5
  • 4b. Paired fins absent.Go to 6

63
Example of Dichotomous Key
  • 6a. Skin scales presentClass Reptilia
  • 6b. Skin scales absent.Class Ampibia

64
Review points
  1. Dispersion patterns
  2. Carrying capacity and limiting factors
  3. r and K selection
  4. Natural population cycles
  5. Human effects
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