Important course Important course information information • 3 lectures; 2 pracs per week (see timetable) • Evaluation – Class test (33%) + Prac work (67%)= course mark – Course mark (60%) + Exam mark (40%) = final mark – TESTS: • (1) Friday 25 th April 1pm Z29 • (2) OPTIONAL Saturday 3 rd May 8am Z29 – CONTINUOUS ASSESSMENT • Report 1 (10%): Estimating population sizes for different organisms (essay OR presentation) – DUE DATE: April 14 th • Report 2 (10%): Determining the age of individuals in a population (essay OR presentation) – DUE DATE: May 5 th • Report 3 (20%): Practical report..mark-recapture – DUE DATE: May 12 th – Exam = open book
Transcript
Important course informationImportant course information
• 3 lectures; 2 pracs per week (see timetable)• Evaluation
– Class test (33%) + Prac work (67%)= course mark– Course mark (60%) + Exam mark (40%) = final mark– TESTS:
• (1) Friday 25th April 1pm Z29• (2) OPTIONAL Saturday 3rd May 8am Z29
– CONTINUOUS ASSESSMENT• Report 1 (10%): Estimating population sizes for different organisms
(essay OR presentation)– DUE DATE: April 14th
• Report 2 (10%): Determining the age of individuals in a population (essay OR presentation)
– DUE DATE: May 5th
• Report 3 (20%): Practical report..mark-recapture– DUE DATE: May 12th
– Exam = open book
Important course informationImportant course information• PASS = Final mark ≥ 50% AND Exam mark ≥ 40% AND
Practical mark ≥ 50%– Supplementary exam – conditional– If Prac mark ≤ 50% OR Course mark ≤ 40% …then not eligible
• EVEN number – Report 1: Presentation (April 14th)– Report 2: Essay (May 5th)
– Report 1: Review the literature and provide a summary of the methods used to estimate the population size of your organism
– Report 2: Review the literature and provide a Summary of the methods used to estimate the age of individuals of your organism
Important course informationImportant course information• Reports must include:
– Brief description of organism – biology, ecology, distribution and habitat– An overview of the methods used for estimating populations– A FULL bibliography
• One to be written as an essay, one to be delivered as PowerPoint presentation• ESSAYS
– 750 ≤ 1000 words (excl. references)– Must reference at least one journal article, maximum of 3 textbook articles
and 3 internet articles– MUST attach copies of referenced text to your report (print/photocopy
appropriate page and highlight cited text)– Reference any illustrations you use
• PRESENTATIONS– 5 minute presentation to be given to the class– Max 5 slides– Must give slides to course co-ordinator 24 hours in advance (Report 1 - 11
April)– See rubric for presentation assessments
• NO MATHEMATICAL FORMULAE in ESSAY OR PRESENTATION. Focus on gathering information on all the types of field or simulation methods used to collect data
Important course informationImportant course information• See handout for evaluation criteria, author instructions and common mistakes• PLAGIARISM
– Offence 1: Zero for submitted work + written apology to department– Can resubmit, but will get maximum 50% for the work – Offence 2: Reported to University Proctor, possible disciplinary action– Sign course plagiarism declaration and submit now.– Assignment plagiarism declaration to be submitted with ALL assignments – Attach paper copies of all cited text to your assigments
• RECOMMENDED READINGS– Begon, M., Harper, J.L. and Townsend, C.R. (1990). Ecology: Individuals,
Populations and Communities. Blackwell Scientific Publications, 945pp. – Begon, M. and Mortimer, M. (1986). Population Ecology: A Unified
Study of Animals and Plants. Blackwell Scientific Publications, 220pp. – Ebert, T.A. (1999). Plant and Animal Populations: Methods in
620pp. ***– Sutherland, W.J. (2000). Ecological Census Techniques: A Handbook.
Cambridge University Press, 336pp– Zar, J.H. (1984) Biostatistical Analysis. Prentice-Hall
*** Must make personal copies of chapters 2 and 4
Important course informationImportant course information• Students taking the course as an elective…if you decide to de-register
from the course, you must do so by the end of THIS week.
• Online resources:
• http://www.bcb.uwc.ac.za– Click on resources
– Click on Online resources
– Follow links to BCB241 2008
– Lecture slides will be made available online at the end of each lecture block
POPULATION DYNAMICS POPULATION DYNAMICS
Required background knowledge:
• Data and variability concepts
• Measures of central tendency (Mean, median, mode, variance, Stdev)
• Normal distribution and SE
• Student’s t-test and 95% confidence intervals
• Chi-Square tests
• MS Excel
THE SCIENTIFIC METHOD
Hypothetico-deductive approach (Popper) based on principle of falsification: theories are disproved because proof is logically impossible. A theory is disproved if there exists a logically possible explanation that is inconsistent with it
Model Explanation or theory (maybe >1)
Hypothesis Prediction deduced from modelGenerate null hypothesis – H0: Falsification test
Test Experiment•IF H0 rejected – model supported•IF H0 accepted – model wrong
Pattern Observation Rigorously Describe
**
*
StatisticsCan only really test hypotheses by experimentation
Notiluca give off light when disturbed
Pattern Observation
Rigorously Describe
Model Explanation or theory (maybe >1)
Give off light when attacked by copepods to attract fish (to eat the copepods)
Hypothesis Prediction deduced from modelGenerate null hypothesis – H0: Falsification test
H0: Bioluminescence has no effect on predation of copepods by fish (or decreases predation)
H1: Bioluminescence increases predation of copepods by fish
TestExperiment•IF H0 rejected – model supported•IF H0 accepted – model wrong
EXAMPLE OF THE SCIENTIFIC METHOD
DESCRIBE
DATAthe raw material of
Science
DATA VARIABILITY
DATA – the raw material of Science
Data pl (datum, s) are observations, numerical facts
Nominal data – gender, colour, species, genus, class, town, country, model etc
Continuous data – concentration, depth, height, weight, temperature, rate etc
Discrete data – numbers per unit space, numbers per entity etc
Often referred to as VARIABLES because they vary
Types of Data
The type of data collected influences their analysis
Male Female
Blue Red Black White
100 g 200 g
121.34 g 162.18 g 180.01 g
5 people
DESCRIBE
DATAthe raw material of
Science
DATA VARIABILITY
VARIABILITY – key feature of the natural world
• Genotypic/Phenotypic variation – differences between individuals of the same species (blood-type, colour, height etc)
• Variability in time/space – changes in numbers per unit space, time
ACCURACY – how close a measure is to the real value
20 cm +
20.63 cm
6 mm +
300 μm +
20.631506542 cm
Accept a level of measurement error: be upfront
VARIABILITY
impossible to describe data exactly
Uncertainty
Accuracy Precision
PRECISION – how close repeat measures are to each other
20.632
19.986
21.102
20.493 20.578
20.710
22.356
20.623
20.755
POPULATION DYNAMICS POPULATION DYNAMICS Required background knowledge:
• Data and variability concepts
Data collection
• Measures of central tendency (Mean, median, mode, variance, Stdev)
• Normal distribution and SE
• Student’s t-test and 95% confidence intervals
• Chi-Square tests
• MS Excel
Population the entire collection of measurements
When taking samples it is vital that they are RANDOM and INDEPENDENT
= Obtain ALL measurements
SMALL POPULATION
=
LARGE POPULATION
Obtain ALL measurementsTake SAMPLES
REPLICATES
= AVERAGE measure
REPRESENTATIVE of POPULATION
e.g.• mass of 19 yr old elephants• the blood pressure of women between 16-18 yrs of age• number of earthworms on UWC rugby field• height of UWC BSc II students• oxygen content of water
DATA COLLECTION
500
m
500 m
e.g. How many earthworms in the field
of 25 0000 m2?
100 m
100 m
A
B
C
D
How many earthworms in the field of 25 0000 m2?
SAMPLE
REPLICATESREPLICATES
REPLICATES
Earthworms
A – 1 (25 in the field)B – 17 (375 in the field)C – 10 (250 in the field)D – 4 (100 in the field)
