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Part C: The Biosphere
Unit 1: The dynamics of Biological Populations
Biological Populations
All organisms, including humans are organized into populations, which are themselves grouped
into communities and form ecosystems. In sociology and biology, a population is the collection
people or organisms of a particular species, living in a given geographic area (or space), at a
given time. These are usually measured by a census. In biology, an isolated population
denotes a breeding group whose members breed mostly or solely among themselves, usually
as a result of physical isolation from other populations. However, they could biologically breed
with any members of the species. A metapopulation is a group of sub-populations in a given
area, where the individuals of the various sub-populations are able to cross uninhabitable areas
of the region.
A population is a group of organisms of a particular species living at a particular place at
a particular time.
For example the population of frogs living in the Maltese Islands is divided into metapopulations
for example, the subpopulation at Chadwick Lakes, at Wied il-Ghasel, etc.
Populations of different species are grouped together to form a community. Therefore a
community is a group of populations of different species living in the same place at the same
time, and which interact with each other. Thus for example, a community of organisms living in
a freshwater rockpool would consist of several populations of plants and animals such as the
frog, the wild mint, the water beetle.
Individuals within a community interact with each other and the physical characteristics of the
surrounding environment to form an ecosystem. Ecosystems are organized together into
biomes, which together form the biosphere, that is the place on earth were living organisms
are found. The biosphere is the part of a planet's outer shell, including air, land, surface rocks
and water, within which life occurs, and which biotic processes in turn alter or transform. From
the broadest geophysiological point of view, the biosphere is the global ecological system
integrating all living beings and their relationships, including their interaction with the elements of
the lithosphere, hydrosphere, and atmosphere. This biosphere is generally thought to have
evolved, beginning through a process of biogenesis, at least some 3.5 billion years ago.
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1. Factors affecting population size
Populations are affected by a variety of factors which either input individuals into a system or
else remove them. These factors are births, deaths and migration.
1.1 Birth Rate
Birth is the process by which an offspring is produced from the body of the mother thus
increasing the size of a population. Birth is a result of either sexual reproduction as in animals
and plants, or asexual reproduction (such as binary fission) such as occurs in protists and
other unicellular organisms (e.g. Paramecium). Sexual reproduction is rather more complex and
results in offspring developing within or outside the female after fertilization by a male. This
takes three forms that is
ovipary (lays eggs, offspring
hatch from eggs), vivipary
(young born directly from
mother) or ovovivipary (eggs
hatch in mother which gives
birth to live young.
The birth rate (natality) is
often
used
to
describe
populations and countries, that is the number offspring born per unit time (usually a year). It is
given the following formula:
N
n
offspring

t time( year )
In demography (the study of populations), the crude birth rate (CBR) of a population is the
number of childbirths per 1000 persons per year. It can be mathematically represented by:
where n is the number of childbirths in that year, and p is the current population.
In general, the natality and crude natality are an indicator of the state of a natural population
since they give an indication of the fertility (the ability of females to bear offspring). When high,
recruitment is occurring, thus showing that a population is healthy, whereas when low, the
population may be unhealthy. To note, however, is that natality changes with seasons since
animals are not fertile throughout the year.
Other indicators of fertility are frequently used such as the total fertility rate that is the average
number of offspring born to each female over the course of her life. In general, the total fertility
rate is a better indicator of (current) fertility rates because unlike the crude birth rate it is not
affected by the age distribution of the population (that is the different ages of the population,
especially females). Yet other methods of measuring birth rate are applicable to humans, such
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as the General fertility rate (GFR), which measures the number of births per 1000 women
aged 15 to 45 (the child bearing age).
Human populations are different than biological populations. In fact, natality is rather constant
throughout the year since women are fertile throughout the year, although events may cause
changes such as booms in offspring. Also, fertility rates tend to be higher in less economically
developed countries and lower in more economically developed countries.
1.1.2 Factors affecting Birth Rate
Several factors affect biological populations namely the level of resources (be they nutrients,
females, light, prey) and the climatic conditions of the particular time. Once again, human
populations are affected differently since they are more complex. Therefore humans are affected
by the following:
- Pro-natalist policies and anti-natalist policies from government;
- Existing age-sex structure;
- Social and religious beliefs - especially relation to contraception;
- Female literacy levels;
- Economic prosperity (although in theory when the economy is doing well families can
afford to have more children in practice the higher the economic prosperity the lower the
birth rate);
- Poverty levels – children can be seen as an economic resource in developing countries
as they can earn money; and
- Infant Mortality Rate – a family may have more children if a country's IMR is high as it is
likely some of those children will die.
1.2 Death Rate
Death is the full cessation of vital functions in the biological life. It is expressed as the death rate
(mortality) and is calculated
through the following formula:
M 
n
deaths

t time( year )
Mortality is the number of deaths
(from a disease or in general) per
1000 individuals and is typically
reported on an annual basis in
humans. It is distinct from
morbidity rate, which refers to the number of individuals who have a disease compared to the
total number of individuals in a population.
Several other definitions occur:
- The crude death rate: the total number of deaths per 1000 people. The formula is:
CDR 
n
1000
P
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-
The perinatal mortality rate: the sum of neonatal deaths and fetal deaths (stillbirths) per
1,000 births;
The maternal mortality rate: the number of maternal deaths due to childbearing per
100,000 live births.;
The infant mortality rate: the number of deaths of children less than 1 year old per
1000 live births; and
The standardised mortality rate (SMR) or age-specific mortality rate (ASMR): This
refers to the total number of deaths per 1000 people of a given age (e.g. 16-65 or 65+);
The mortality is often indicative of the state of the population. A high death rate means the
population is in decline while if the death rate is low, the population is probably sound.
However, the crude death rate as defined above and applied to a whole population can give a
misleading impression. For example, the death rate differs between the three life groups of
humans and thus one would rather use ASMR. The ASMR reveals that in underdeveloped
(developing) countries, infant mortality rate is high compared to developed countries. Also, for
example the number of deaths per 1000 people can be higher for developed nations than in
less-developed countries, despite standards of health being better in developed countries. This
is because developed countries have relatively more older people, who are more likely to die in
a given year, so that the overall mortality rate can be higher even if the mortality rate at any
given age is lower. A more complete picture of mortality is given by a life table which
summarises mortality separately at each age. A life table is necessary to give a good estimate of
life expectancy.
A life table (also called a mortality table or actuarial table) is a table which shows, for a
person at each age, what the probability is that they die before their next birthday. From this
starting point, a number of statistics can be derived and thus also included in the table:
- the probability of surviving any particular year of age
- remaining life expectancy for people at different ages
- the proportion of the original birth cohort still alive.
Life tables are usually constructed separately for men and for women because of their
substantially different mortality rates. Other characteristics can also be used to distinguish
different risks, such as smoking-status, occupation, socio-economic class, and others.
An example of a life table is given on the following page.
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1.2.1 Infant mortality
The infant/ offspring mortality is often an indication of the vulnerability of a species. For
example, oysters produce 100million eggs, only 1 of which survives to adulthood. Larger
organisms such as elephants produce 6 offspring of which approximately 2 survive. In terms of
human populations, infant mortality is a clear indication of the how much a population is
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developed. The international levels of infant mortality, depicted as the number of deaths in a
thousand births.
The ten countries with the highest infant mortality rate are:
1. Angola 192.50
2. Afghanistan 165.96
3. Sierra Leone 145.24
4. Mozambique 137.08
5. Liberia 130.51
6. Niger 122.66
7. Somalia 118.52
8. Mali 117.99
9. Tajikistan 112.10
10. Guinea-Bissau 108.72
1.2.2 Causes of Death
In biological populations, causes of death are natural including age, predation, parasitism and
disease. On the other hand, in human populations natural and induced deaths are
distinguished. Natural deaths are death due to age but induced to deaths are due to diseases.
For example the 10 leading causes of death in the United States in 2002 were:
1. 696,447 Heart disease;
2. 557,197 Malignant Neoplasms (i.e. cancer)
3. 162,555 Cerebrovascular disease
4. 124,777 Chronic low. respiratory disease
5. 105,796 Unintentional injury
6. 73,248 Diabetes mellitus
7. 65,418 Influenza & pneumonia
8. 58,866 Alzheimer's disease
9. 40,801 Nephritis
10. 33,569 Septicemia
The factors affecting a country's death rate are:
- Nutrition levels;
- Standards of diet and housing;
- Access to clean drinking water;
- Hygiene levels;
- Levels of infectious diseases;
- Large scale events and natural disasters.
1.3 Migration
Migration occurs when living things move from one biome to another. Immigration is movement
into a biome, and emigration is movement out from a biome. Therefore, immigration increases
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the size of a population, whilst emigration decreases it. The species that periodically migrate are
called migratory, those that do not are called resident (or sedentary).
A typical example is bird migration which is very common. The longest known migration of a bird
is that of the Arctic Tern, which migrates from the Arctic to the Antarctic and back each year.
Flyways are routes that certain bird species take to migrate. Whales and other animals, such as
gnus, butterflies, moths, salmon, eels, and lemmings are also known to migrate. The periodic
migration of plagues of locusts is a phenomenon recorded since Biblical times.
1.3.1 Causes of Migration
Several causes of migration occur. Organisms migrate in order to avoid local shortages of food,
usually caused by winter. Animals may also migrate to a certain location to breed, as is the case
with some fish. Therefore, organisms move from an unfavourable environment into a more
favorable one to survive.
In human history, migration was very common. Colonization of Europe by early hominids was by
migration from Africa, as was colonization of America. The main migration routes of humans are
given below.
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1.4 Population Growth Rates and Doubling Time
1.4.1 How a Population Grows
When a population is placed in a new habitat (such as Paramecium in a newly formed pond)
and all necessary nutrients are being supplied, the population goes through several changes
depicted through the following sigmoid graph (two examples are given):
The graph is composed of four parts.
Phase 1 (A-B): Lag phase. The population is introduced into a new habitat. The introduced
individuals must adapt themselves(acclimatize) to the new habitat. In doing so they do not
reproduce and their numbers might decrease.
Phase 2 (B-C): Log or exponential phase. Unlimited population growth occurs after the initial
acclimatization period. Abundant food is present, no disease, no predators etc. Therefore
natality and immigration are high whilst mortality and emigration are low.
Phase 3 (C-D): Decline or transitional phase. Limiting factors slowing population growth. Due
to increased density, resources such as food start to decrease. Therefore mortality and
emigration start to increase and natality and immigration decrease.
Phase 4 (D-E): Plateau or stationary phase. No growth. The limiting factors balance the
population’s capacity to increase. The population reaches the Carrying Capacity (K) of the
environment. At this point, recruitment is approximately equal to mortality and
iemigration.
1.4.2 Population Growth and Doubling Time
The rate of growth is expressed as a percentage for each population, commonly between about
0.1% and 3% annually for countries. You'll find two percentages associated with population natural growth and overall growth. Natural growth represents the births and deaths in a
country's population and does not take into account migration. The overall growth rate
takes migration into account.
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For example, Canada's natural growth rate is 0.3% while its overall growth rate is 0.9%, due to
Canada's open immigration policies. In the U.S., the natural growth rate is 0.6% and overall
growth is 0.9%. For most purposes, the overall growth rate is the more frequently utilized.
The growth rate can be used to determine a country or region or even the planet's doubling
time, which tells us how long it will take for a country's current population to double assuming a
constant rate of natural increase (RNI). The doubling time of a given population in a certain
area is thus the time in years it takes for that population to double its size given its current
population growth.
This time can be found either from a graph or from a simple equation:
In this equation, often referred to as the law of 70, k is the fractional growth rate (the annual
growth rate per unit of time as given under exponential growth), P is the percent growth rate
(100 times the fractional growth rate. This is the percent by which a quantity grows in a set time
period), and TD is the doubling time. 70 is obtained through the natural logarithm (ln) of 2.
For example, given Canada's overall growth of 0.9% in the year 2006, dividing 70 by 0.9 (from
the 0.9%) will yield a value of 77.7 years. Thus, in 2083, if the current rate of growth remains
constant, Canada's population will double from its current 33 million to 66 million. This is an
accurate estimate because of recent trends.
In natural populations, animals which have a high fertility rate (the average number of offspring
each female will have during their offspring-bearing age) such as mice, have a low doubling
time, whereas animals with a smaller fertility rate, or else their offspring have maternal ties (such
as mammals) have a long doubling time.
In humans the situation, as usual, is slightly different. The map on the following page gives the
approximate doubling time for countries. It shows how long it will take for the population to
double in size assuming it continues to grow at the current rate. The darker the colour, the
longer the doubling time. For example, the United Kingdom at 433 years has a longer doubling
time than Madagascar at 21 years. Green shading on the map indicates that the population is
decreasing or that no information is
Taking for example the African countries, doubling time is low, whereas European countries
have a larger doubling time. This is linked to the generation of more offspring in less developed
countries.
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The information below is taken from the Population Concern 1997 World Population Data Sheet.
Countries are in order of Doubling Time (years):
Rank Country
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Sweden
Greece
Portugal
Spain
Austria
Denmark
Moldova
Belgium
Poland
United Kingdom
Slovakia
Japan
San Marino
Yugoslavia
Finland
Switzerland
Netherlands
Doubling
Time
(years)
4077 years
1733 years
1733 years
1386 years
990 years
990 years
866 years
693 years
573 years
433 years
408 years
289 years
289 years
279 years
257 years
231 years
223 years
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Barbados
France
Georgia
Norway
Luxembourg
Ireland
Liechtenstein
Malta
Kazakhstan
Canada
Bosnia-Herzegovina
United States
Armenia
Cuba
Australia
Cyprus
Macedonia
New Zealand
204 years
204 years
204 years
204 years
178 years
147 years
139 years
136 years
133 years
127 years
122 years
116 years
108 years
102 years
100 years
90 years
86 years
86 years
Countries with high birth rates and low death rates have the fastest rates of growth and
therefore the shortest doubling times. This is the number of years it will take for a population to
double in size if the current rate of increase continues. However, alternatively, the doubling time
for a countrywith low birth rate and high mortality rate is high. The doubling time can therefore
be compared with the total fertility rate, that is the average number of children each woman in
that country will have, assuming that the birth rate stays the same throughout her child-bearing
years (15-49).
Taking, for example the situation in West Africa, the following is observed:
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Country
Total Fertility Rate
TFR
Doubling Time
DT
Life Expectancy
(no. of children)
Rank
(years)
Rank
(years)
Benin
6.8
21
Burkina Faso
6.9
23
11
47
Cape Verde
3.8
16
36
1.5
65
Cote d'Ivoire
5.7
12.5
27
52
Gambia
5.9
28
45
Ghana
5.5
24
Guinea
5.7
GuineaBissau
12.5
54
9
56
29
45
5.8
34
43
Liberia
6.4
22
59
Mali
6.7
23
Mauritania
5.4
27
52
Niger
7.4
21
47
Nigeria
6.2
Senegal
6.0
Sierra Leone
6.5
36
1.5
34
Togo
6.9
20
16
57
1
23
9
11
11
26
46
54
49
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Exercise 1: Is there is a link between doubling time and total fertility?
1 Rank both sets of data in the correct column (longest doubling time = rank 1; highest total
fertility = rank 1).
2 Plot the rank position for each country as a point on a
scatter graph like the one on the right. Name each point as
you go.
3 Add the labels 'Lowest Fertility Rate' and 'Highest Fertility
Rate' at the correct ends of the side axis. Add 'Longest
Doubling Time' and 'Shortest Doubling Time' to the bottom
axis.
The points should form a band from the top left to the bottom
right. If the link between total fertility rate and doubling time
was perfect, all the points would be on the diagonal line. In this case only one country,
__________ is on the line, but the spread still shows a negative link or negative correlation.
This means that as one thing increases, the other thing decreases. In this case, as
________________________ increases _______________ decreases.
The fact that some countries are far from the diagonal line shows that there must be other
factors affecting the situation, ie. that total fertility rate is quite a good predictor of doubling time,
but that there must also be links with other factors.
4 Countries whose position is away from the line in segment A of the graph have doubling times
which are quite long given their fertility rates, eg. Guinea.
Countries in segment B, like Ghana, have short doubling times not in keeping with their modest
fertility rates. Suggest some factors which might make the doubling time shorter than expected.
5 Life expectancy is the number of years a person born in that country can expect to live. The
shortest life expectancy in West Africa is just _____ years. The longer life expectancy in Liberia
(_____ years) suggests that the standard of living and public health services are better than the
average for the region. Many countries in the more developed world are noted for their excellent
life expectancy - check out Sweden, Norway, Canada, the UK and Iceland using the World
Population Data Sheet. Notice that women tend to live longer than men. See if your teacher can
explain that!
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2. Population Growth
Population growth is change in population over time, and can be quantified as the change in the
number of individuals in a population per unit time. In demographics and ecology, Population
Growth Rate (PGR) refers to the change in population over a specific time period expressed as
a percentage of the number of individuals in the population at the beginning of that period. This
can be written as the formula:
2.1 Factors Affecting Population Growth
Over time, assuming that resources (food and space)
are available, the intrinsic nature of any population is to
grow! Surpluses and increases in food availability
allow populations to grow at exponential rates.
However, populations have a limit to the rate of growth
and they can undergo and to the size of the population
that can be attained. Several factors contribute to the
size of a population namely environmental
resistance.
In naturally occurring systems, resources do not
continually increase over time. Biological events
(environmental resistance) occur that allow a
population to stabilize and be in balance with
resources. The environmental resistance is thus
the limiting influences of environmental factors
upon the increase in numbers of individuals in a
population.
Environmental resistance falls within three
categories:
- Abiotic
(non-biological)
factors
that
contribute to limiting a population size include
examples such as: wind (gentle breezes vs. tornados), rain (drought vs. flood), rain pH, amount
and quality of sunlight, climate, lightning, fire.
- Biotic (biological) factors that contribute to limiting a population size include examples
such as: disease, resource availability, predators, Competitors.
- Social factors contribute to limiting the size of a population within species that have social
systems. The social system of flocking birds is hierarchical. The relationship among birds is
categorized as: dominant, sub-dominant and juvenile. A birds place in the "pecking order" will
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determine whether it has a high, medium or low quality environment to exploit. The quality of
the environment will determine whether the bird thrives or merely survive.
In general these three types of resistance can be defined as being density-dependent (biotic,
social) or else density- independent (abiotic, biotic, social). In the former, resistance
increases with increasing density of the population and in the latter, density does not have a
role.
2. 2 Density dependent and Density- Independent factors
Density-Independent factors are factors acting randomly, with reference to the population
density, to regulate population size. These do not depend on the size of a population and
examples are:
1) Weather - unfavourable weather can limit breeding success or cause mortality during the
non- breeding season (e.g., winter mortality).
2) Food Supply - abundance of food is often dependent on climatic factors, and in poor years
food supply may limit population size.
3) Habitat Limitation - seasonal, annual, or anthropogenic changes can affect resource levels
such as nesting sites or availability of nesting materials.
(2) and (3) contribute to setting a limit on the Carrying Capacity of the habitat.
Density-Dependent Factors regulate populations according to the population density. Therefore
they increase with increasing population size and include:
1) Predation: Acts more strongly at high densities. Keeps populations below the theoretical
carrying capacity in some cases.
2) Competition: if resources are limiting, only a given number of individuals may persist in a
given habitat (the number that can persist is the carrying capacity). At low densities competition
is not an important factor in regulating population size, but at high densities (near the carrying
capacity) it becomes very important.
3) Parasites and Disease: have the greatest effect at high population densities. Can be
important factors regulating population sizes in some cases. Example: Avian cholera can kill
very large numbers of wintering or migrating waterfowl that are concentrated in relatively small
areas.
2. 3 The Carrying Capacity
The maximum population size that can be attained under specific conditions is termed the
carrying capacity (K). This is the maximum population size that may be maintained indefinitely
(for a long period of time) by the present resources of a certain environment.
2. 4 The Biotic Potential
Biotic potential is the maximum reproductive capacity of an organism under optimum
environmental conditions. Full expression of the biotic potential of an organism is restricted by
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environmental resistance. A species reaching its biotic potential would exhibit exponential
population growth and be said to have a high fertility.
Biotic Potential is a fundamental species characteristic, defined as "the inherent power of
organisms to reproduce and survive". It is the sum of the number of young produced at each
reproduction, number of reproductions over a period of time, sex ratio of the species, and their
general ability to survive under given physical conditions. Therefore, the components of Biotic
Potential are the Reproductive potential (potential natality; It is the upper limit to biotic
potential, that is in the absence of mortality) and the survival potential
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3. Models of Population Growth
Populations grow if the natality and immigration exceed the mortality and emigration.
Populations decrease in nature if the opposite occurs. Populations in nature may grow in several
different ways, described by mathematical models. Four common models are described below.
These are the Linear growth, Irruptive growth models, Exponential (density independent) growth
and Logistic (Sigmoid) growth). The latter two are called the Lotka-Volterra Models.
3.1 Linear growth (Density independent)
A population starts off with a small
number of members. Since numbers
are small, the population increases in
size very slowly. The population
increases in a slow manner,
increasing in a linear fashion, that is,
the increase in individuals is linear
over time. Therefore, birth rate and
immigration are higher than mortality
and emigration in a constant manner.
3.2 Exponential growth (Density independent)
In this type of growth, a population starts off with a
small number of members. Since the numbers are
small, the population increases in size very slowly.
When the population increases above a certain
level, it quite suddenly starts to grow very rapidly,
possibly at its maximum rate of growth
(recruitment). This is exponential growth, and goes
on for as long as there is enough room and enough
food for all the members of this rapidly expanding
population.
3.3 Logistic/ Sigmoid growth (Density dependent population)
The population grows roughly exponentially to begin with, but then rise more slowly towards a
“carrying capacity”. Thus, when the population increases to a certain level space and food start
running out. The individuals in the population become more crowded, food is scarce and
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disease spreads rapidly. Therefore, the natality and
immigration decrease and mortality and emigration
decrease. Eventually these two become equal and the
population levels off. The rate of population growth slows
down and stabilizes at a certain level called the carrying
capacity.
3.4 Irruptive (Malthusian growth)
Some populations do not follow this pattern of growth and stabilisation. Some populations start
off small, start to grow exponentially after a while and keep on growing. They may grow so
rapidly and become so large that they may exceed the carrying capacity (the maximum amount
that can be maintained by the environment). This is called overshoot. When a population
overshoots, resources used by members of the population run out very quickly. This is therefore
followed by a dieback, where high rates of mortality occur. This means that the population would
fall back to its previous levels. This is called irruptive growth or Malthusian growth.
Irruptive growth, is thus a growth pattern defined by population explosions and subsequent
sharp population crashes, or diebacks. Populations which exhibit irruptive growth do not
stabilize around their carrying capacity but are subject to continual change. An example is given
by locusts whereby populations may be low but suddenly increase rapidly forming swarms,
which eventually die. This is also seen in some mammals such as lemmings.
3.5 Other Models
3.5.1 Two-species competition
Each population grows logistically in the absence of
competition, with its growth rate reduced as its
population gets bigger. When a competitor is present,
then the growth of each population is further reduced
by the other. The outcome depends on the relative
strength of interspecific competition
The graph shows that both species initially grow at
similar rates, but then species 1 escapes and
suppresses species 2.
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3.5.2 Predator – prey
The prey
grows exponentially in the
absence of predation. It is predated at a rate
proportional to the number of predators. The
growth rate of the predator population is
proportional to prey consumption, and
predator mortality is proportional to its
population.
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