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Ecology and Environment Management
POPULATION CHARACTERISTICS
Dr Dharam Vir
Department of Zoology
K.M. College
University of Delhi
Delhi – 110 007
Date of Submission: 09.07.2006
Contents:
1. Density, Natality, Mortality, Life-table, Survivorship curves, Age distribution, Sex
ratio, Dispersal,
2. Dispersion and Innate capacity for increase in numbers.
3. Human population growth, Demographic transition, Growth rate, growth forms,
Exponential growth, Logistic growth, population fluctuations and cycles, and
Population regulation.
POPULATION CHARACTERISTICS
Usually the organisms live in groups. But when they live solitary lives even then they interact
with other members of the same or other species at different times in their lives. Each species in
an ecosystem exist as a population. Within the population, all the individuals capable of
reproduction have the opportunities to reproduce with other members of the same species. Thus
a population is defined as a group of interbreeding or potentially interbreeding organisms
occupying a particular space at the same time. Tiger population of Jim Corbett Park
(Uttrranchal) and lion population of Gir forest (Gujarat) are the example of tiger and lion
population in the respective areas.
The species population may have numerous subpopulations or demes also called as local
populations. Deme is defined as a group of interbreeding organisms and is the smallest
collective unit of animal population. All the individuals in a local population share a common
gene pool. Since the population is composed of interbreeding organisms, a population is a
genetic unit, as each individual carries a certain combination of genes. The gene flow
(exchange of genetic information) between populations occurs through immigration and
emigration. Populations may act as evolutionary units and the natural selection acts on the
individual organism leading to its evolution due to change in gene frequency over a period of
generations. It may change the physical expression of organisms in the population. Thus
population ecology and population genetics are influenced and regulated by each other.
A population has various group characteristics, which are best expressed as statistical functions.
These functions are unique to the group and cannot be applied to the individuals in the group.
Some of these properties are density, natality, mortality, age distribution, biotic potential,
dispersion, dispersal and growth forms. Population also has certain genetic characteristics
related to their ecology and these are adaptiveness, reproductive fitness and persistence i.e.
survival of the race over long period of time
A brief description of the statistical properties of the population is given below:
DENSITY ;
It is defined as population size in relation to some unit of space. It is expressed either in terms
of individuals or biomass/area or volume e.g. 500people/ square km or 5000 crustaceans/m3 of
water.
Density of the organisms in an area varies with the seasons, food supply and climatic conditions
but has definite upper and lower limits. The upper limit to density is imposed by the size of the
organism and its trophic level (2nd law of thermodynamics). Smaller the organism, greater is its
abundance / area e.g. a part of a particular forest is able to support more wood mice than deer
population but reverse may not be true. The lower limit is not well defined but homeostatic
mechanisms keep the density of the organisms within the limit. Density is an important
population characteristic and is dependent upon a number of factors like energy flow, resource
availability and utilization, physiological stress, dispersal and productivity of the population.
The important factors responsible for change in the density of a population are integrated as
shown below:
IMMIGRATION
+
↓+
NATALITY →
-
DENSITY → MORTALITY
↓-
EMIGRATION
Population density is of two types:
Crude density: It is defined as the number of individuals or biomass/unit of the total space e.g.
the number of Rhinoceros living in the Kaziranga National Park.
Specific or Ecological density: It is defined as the number or biomass/ unit of the habitat space
(available area or volume that can be actually colonized by the population). Generally,
populations do not occupy all the space within a unit as whole of it may not be habitable. So we
may estimate the number of Rhinoceros/sq. mile but it may avoid some of the area because of
the lack of food, shelter and human habitations. Therefore, the area inhabited by the Rhinoceros
actually will be its ecological density.
The difference between crude and ecological density can be explained by taking the example of
a fish pond. The density of the fish in the pond decreases as the water level drops during the
summer season but the ecological density in the decreasing water of pond increases, as the fish
are crowded into smaller and smaller water area. It becomes very easy for the predatory bird to
catch fish at this time of the year as the ecological density of the fish is at its peak.
Methods of measuring density: Absolute density can be measured by some of the methods
given below:
Total counts: Just take the headcounts of all the organisms in a given area e.g. conducting
census of human population. In territorial birds, density can be measured by counting all the
singing birds in an area.
Sampling methods: Usually, a small proportion of the population is counted and this sample is
used to estimate the total population. Sampling can be done in two ways.
Use of quadrate: It is a sample area of any shape though the word literally means a four-sided
figure. In this method we count all the individuals on several quadrates of known size and
extrapolate the average to the whole area. The method is extensively used for plant populations
and many invertebrates.
Capture- recapture method: The animals are captured, marked and released in the
environment. The population at any time will have marked and unmarked individuals. The
proportion of marked individuals in a later sample is used to determine the total population
However, sometimes it is difficult to determine the absolute density of a population and it is
simple to find the relative density. The relative density does not provide an estimate of density
but it is rather an index of abundance that is more or less accurate. It may be time relative as
number of birds seen / hour, or the area “X” has more organisms than “Y”. Relative density
can be measured by the following methods:
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Traps: They are generally used in capture- recapture methods but can also be used to get an
index of relative density as the number of individuals’ caught/ day/trap.
Number of fecal pellets: By knowing the number of fecal pellets in an area and the average
rate of defecation, we can get an index of population size. It is used for the population of
rabbits, deer and field mice etc.
Vocalization frequency: The number of pheasant calls heard/15 minutes in the early morning
has been used as an index of the size of the pheasant population.
Questionnaires: They can be sent to sports person or trappers to get an estimate of population
changes.
Feeding capacity: The amount of bait taken by rat/mice can be measured before and after
poisoning and can be used as an index of change in density.
Road side counts: The number of birds of prey observed while driving a standard distance can
be used as an index of abundance.
NATALITY:
It refers to birthrate of a population. Natalities in general cover the production of new
individuals whether they are born, hatched, germinated or arise by fission. Natality is of two
types:
Maximum, Absolute or Physiological Natality: It is the theoretical maximum production of
new individuals under ideal conditions and is constant for a given population. However, this
number is rarely achieved in wild populations, but by observing the reproductive rate of a
population under favorable conditions or when major limiting factors are temporarily
nonoperative, we can observe the maximum natality of a population, e.g. if a small group of
paramecia is placed in a fresh medium under favorable conditions, the maximum reproductive
rate achieved will give its maximum natality. Maximum natality is useful for two reasons.
It provides a standard for comparison with realized natality.
As a constant, it is useful in setting up equations to predict the rate of increase in a population.
Ecological or Realized Natality: It refers to population increase under actual or specific
environmental conditions. It is not constant for a population and varies with the size, age,
composition and physical environmental conditions of the population.
Natality can be expressed as:
∆ Nn/ ∆t
Or ∆ Nn/ N ∆t
=
Absolute/ crude natality/birth rate
=
specific natality/ birth rate i.e. the number of new
Individuals/ unit time/ unit population
N
=
Total population or only the reproductive part of the
population
Nn
=
New individuals added to the population
∆t
=
time lapsed during change in population
Crude natality / birth rate is expressed in terms of population size e.g. 40 births /1000
individuals of the population. The specific birth rate will be 4 %.
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In higher organisms, N can be defined as age specific natality for different age groups in the
population e.g in a study of wild rabbit population, it was found that 1 or 2 years female on an
average produced 4 youngs/year/female. But this age specific rate was 1.5 in less then 1-yearold rabbits.
Since population increase depends upon the number of females in a population, the age specific
birth schedule counts only females giving rise to females. The age specific schedule is obtained
by determining the mean number of females born in each group of females. We take the data of
survivorship column from the life table and the age specific birth value to determine the net
reproductive rate, Ro. It is defined as the number of females left during a lifetime by a new
born female. Reproductive rate is useful for comparative purposes as it summarizes the
information on the frequency of pregnancy, the number of females born and the length of the
breeding season. The simplest method of obtaining reproductive rate is to count the embryos;
placental scars, the number of eggs and unfledged young ones. Ro is usually modified into
fertility rate, i.e. the number of births/1000 women in the age group of 15- 40 years.
MORTALITY:
It refers to the death of individuals in a population. Two types of mortality can be recognized.
1. Ecological or Realized Mortality is the loss of individuals under given environmental
conditions and varies with the environment and population.
2. Theoretical Minimum Mortality is the loss of individuals under ideal or non limiting
conditions. Therefore, even under the best conditions, individuals would die of old age
determined by their physiological longevity. It is always greater than ecological
longevity. The organisms in nature actually become senescent. Predators, diseases and
other hazards cut down most of them long before they reach old age.
Mortality is the number of deaths per thousand in a given period. Generally, mortality in a
population is expressed either as the probability of dying or as death rate. Death rate is the
number of deaths during a given time interval divided by the average population. For example,
if the population size at the beginning of the period is 500 and the number alive at the end of the
period is 400, the average size of the population for the period will be 900/2 = 450.The number
of deaths is 100, so the death rate is 100/450 = 0.22. The probability of dying is the number that
died during a given time interval divided by the number alive at the beginning of the period, i.e.
100/500=0.2. The complement of probability of dying is the probability of surviving, i.e. the
number of survivors divided by the number alive at the beginning of the period. Since we are
more interested in the number of survivors, mortality can be expressed in terms of life
expectancy, which is the average number of years to be lived in future by the members of a
given age in the population.
Life Table: It is a statistical device, which gives a clear and systematic picture of mortality and
survival in a population, which vary with age and developmental stages. It is widely used by the
life insurance companies to determine the probability of survivorships for deciding the rate of
premium. Ecologists use it in the study of natural populations. Raymond Pearl, (1921) first used
life table for Drosophila populations obtained under laboratory conditions.
A life table gives an age specific summary of mortality rates operating in a population and it has
a series of columns, each describing an aspect of mortality statistics for the members of a
population according to age. The individuals are born at the same time and form a cohort.
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The different columns of a life table are as follows:
X
= age interval or age class
nx
= number of survivors at start of age interval x
lx
= proportion of organisms surviving to start age interval x.
dx
= the number or proportion dying during age interval x to x+ 1
qx
= rate of mortality during the age interval x to x+ 1
Lx
= number of individuals alive on the average during the age interval x to x+ 1.
Tx
= total years to be lived by individuals of age x in the population
ex
= mean expectation of life for individuals alive at start of age interval x
.
Life tables for non-human population are however difficult to get under field conditions. They
are usually biased because the first year age class is not properly accounted for. Life table data
for Balanus population is given below in the Table 1.1.
Table 1.1- Life table for the barnacle (Balanus glandula) at the Upper Shore level on Pile Point,
San Juan Island, Washington (Connell 1970).
Age
(yr) (x)
Observed
No.
Barnacles
Alive
Each
(nx)
Proportion
Surviving at
Start of Age
Interval
x
(l
x)
Year
No. Dying Rate
of Mean
within Age Mortality
Expectation of
Interval x to (qx)
Further Life for
x + 1 (dx)
Animals Alive
at Start of Age
x (ex)
0
142
1.000
80
0.563
1.58
1
62
0.437
28
0.452
1.97
2
34
0.239
14
0.412
2.18
3
20
0.141
(4.5)
0.225
2.35
4
15.5
0.109
(4.5)
0.290
1.89
5
11
0.077
(4.5)
0.409
1.45
6
6.5
0.046
(4.5)
0.692
1.12
7
2
0.014
0
0.000
1.50
8
2
0.014
2
1.000
0.50
9
0
0.0
-
-
-
6
The following types of data have been used in general to determine ecological life table.
Laboratory animals: life tables can be constructed for laboratory animals of known age by
observing the number of individuals dying at regular intervals of time till the population is
exhausted.
Survivorship directly observed: The information on survival of a large cohort is followed at
intervals till its existence. Connell (1961) observed mortality in Chthamalus stellatus at regular
intervals, which grew on rocks in Scotland in the autumn season to construct the life table.
Age structure directly observed: The ecological information on age structure can be obtained
by determining annular rings in the horns of sheep, growth rings in the cementum of teeth of
ungulates and carnivores and annular rings on the scales of fishes. For example, if we fish a
lake, we can get a sample of fish and determine the age of each from annular rings on their
scales. The same type of data can be obtained for tree rings. However, this type of data is not
preferred for constructing life tables.
Human life tables can be constructed on the basis of data of birth and death recorded by
municipal committees under state government and by life insurance companies.
There are three types of life tables:
Horizontal life table (cohort or dynamic life table): following closely a cohort of individuals
makes such life tables and a cohort is a group of individuals all born at the same time. We start
with an initial number of 1000 individuals and go on observing the number dying at intervals
till the population is exhausted. It is applicable to short lived species and the generations are
discrete.
Vertical life table (time specific or static life table): It is based on the assumption that each age
class is sampled in proportion to its numbers in the population and ages at death and that the
death and birth rates are constant and the population is stable.
Dynamic composit life table: It is same as the cohort life table but here the cohort is a
composite of a number of animals marked over a period of years rather than at the time of birth
only.
The static and dynamic composite life tables are inaccurate but the cohort life table gives a fair
idea about the average conditions in the populations. Life tables can be useful in comparing life
history trends within the population and in between different populations.
Survivorship curve: The data from a cohort life table is usually shown as survivorship curve
for a particular population and it depicts age specific mortality through survivorship. This is a
graph, which shows the number of individuals surviving per thousand of a population through
each phase of life. We can represent the life table on a semi- logarithmic paper where the
number of individuals surviving is plotted on vertical axis on a logarithmic scale and time is
shown on the horizontal axis on the arithmetic scale. Survivorship curves may be classified into
three types (Fig. 1.1), which act as standards against which real life life survivorship curves of
different organisms can be compared.
Convex type curve is typical of populations, which tend to live their physiological life span
(type- I). They experience a high degree of survival throughout life and suffer heavy mortality
in the old age. The convex curve is characteristic of many mammals like elk, sheep and
humans.
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A linear curve where age specific survival is nearly constant in organisms. It is characteristic
of adult stages of many birds and rodents (type-II). In holometabolous insects a stair type of
survivorship curve is obtained as survival differs greatly in different stages of life history. In
many birds, rabbits and mice a slightly concave or sigmoid curve occurs because the mortality
is high in the young but low and nearly constants in the adult stages.
Concave curve is typical of organisms that have high mortality rates in early life (type-III) and
is
characteristic of organisms like many insects, fish, oysters and shellfishes. In oysters,
mortality is high due to adverse environmental conditions and predation in the early larval
stages.
The shape of the survivorship curve can be used to pin point the critical periods in the lives of
the organisms. Wherever the curve becomes steeper, there is an increase in mortality indicating
some environmental or developmental effects on the population. Salmon produce thousands of
eggs but only a few survive to reach the adult stage. If one egg in 10,000 survives to become
adult, it means that only 0.01% of the total energy invested is represented in the next generation
of fish. Majority of the animals reproduce this way only. Most large animals are iteroparous
i.e. they live to reproduce repeatedly but many species of insects and microorganisms are
semelparous i.e. after a single reproductive effort one or both the parents die. The reproductive
efforts of a semelparous species represent the ultimate expenditure of energy in order to
produce as many eggs as possible.
Mortality curve: When the data in the qx or mortality rate column of the life table is plotted
against age, a mortality curve is obtained (Fig.1.2). It has two phases:
the juvenile phase, in which the rate of mortality is high and
the post juvenile phase, in which the rate first decreases as age increases and then increases with
age after a low point in mortality.
Generally, the mortality curve is j – shaped and such mortality curve, which indicates the rate of
mortality indirectly by the slope of the line, are more informative then survivorship curve.
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AGE DISTRIBUTION:
The nature and character of a population is influenced by its age structure. It influences both
natality and mortality. The ratio of various age groups in a population is indicative of its
reproductive status. It gives us an idea about the future population projections. Generally, an
expanding population will have large proportion of young individuals, a stable population will
have a more or less even distribution of different age classes and a decling population will be
9
having large proportion of older individuals. A population may pass through changes in age
structure without change in size. Normally a population tries to attain a stable age distribution.
The ratio of various age groups in a population indicates its current reproductive status and the
trends to be expected in future. Usually the ratio of young to adult in a relatively stable
population of most animals is approximately 2:1. Once a stable age distribution is reached,
changes in natality and mortality affect population stability temporarily and it tries to return to
the stable condition at the earliest.
The age distribution can be expressed in terms of three ecological ages i.e prereproductive,
reproductive and post reproductive in birds and mammals (Bodenheimer, 1938) or eggs, pupae,
larvae and instars in insects. For human beings, three ages are relatively equal in length, about
one third of his life falling in each category. In insects e.g. certain species of may flies
(Ephemeroptera) take one to several years to develop in the larval stages in water and the adults
emerge to live for a few days. The 17-year cicada has a long developmental history (not
necessarily 17 years) but the adult life lasts less then one season.
In fishes, which have very high natality rate, a phenomenon known as dominant age class has
been observed. When a large year class occurs because of unusual survival of eggs and larval
fishes, reproduction is reduced in the next several years. Thus the fishes of a particular year
class dominate the catch for a particular of time, peaking and then declining. Other classes may
replace them in subsequent years. However, it is not known as to what environmental factors
result in unusual survival in fishes every now and then.
The age distribution data can be arranged in the form of polygons or age pyramids where the
relative width of the successive horizontal bars shows the number of individuals or the
percentage in different age classes. Accordingly three types of pyramids are recognized (Fig.
1.3).
A pyramid with a broad base represents an expanding population. The population growth is
usually exponential resulting in large number of young individuals.
A bell shaped pyramid represents a moderate proportion of young and old individuals. The
growth rate slows down and the reproductive rate approaches one.
An urn shaped pyramid represents a declining population. The growth rate is further reduced
and less number of young ones is added to the population.
Age distribution is of practical value in wild life management. A low ratio of immature to adults
indicates a poor reproductive season and should caution against excessive yield as the
population is declining. However, change in age distribution alone does not imply change in
survivorship or fecundity and it alone should not be used to predict population trends.
Fig. 1.3 - Expected Shape of Age Pyramids of
a) Expanding Populations (Broad base)
b) Stable Populations
(Bell Shape)
c) Declining Populations (Urn Shape)
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SEX RATIO The animals in a population differ in a number of ways such as sex, age, breeding
condition and health. Sexual reproduction is a characteristic feature of eukaryotes. Some
organisms may be reproducing asexually but still they have provisions for sexual reproduction
in their life cycle as it helps in maintaining genetic variability in the population. Sex ratio refers
to the percentage of male and female organisms in the population.
The sex ratio is of two types:
Primary sex ratio: It is the ratio at the time of conception and it tends to be 1:1.
Secondary sex ratio: it is the ratio at the time of birth. This ratio often favours males but in the
older age it tilts towards females.
Among humans also males exceed females at birth (52%) but as age increases the ratio swings
in favour of females. Similarly in rabbits, cattle and many birds the percentage of males is
higher then females but in domestic chicken, sheep and horse males constitute 49% of the
population. Secondary sex ratio of vertebrates show greater variation e.g. in Alaskan fur seal
one adult bull may dominate a breeding group of 30 females and the male sex ratio is greater
then 3%. The excess adults are at the periphery of the breeding grounds. They are essentially
surplus and suffer high mortality. In some birds, females have higher mortality then the males,
especially in the nesting season. In blue winged teal males are 59%, whereas in mallards and
pintails males outnumber females and the ratio is 4 or 5:1 only.
The reason in shift of sex ratios from 1:1 to unequal at a later stage may be due to physiological
and behavioral patterns, which may affect mortality in different sexes differently. In birds, the
females help males in defending the territory, building the nest, lay and incubate the eggs,
brood and feed the youngs and is more vulnerable to predation and other dangers than males.
The adult males in mammals and adult females in birds spend more energy and are under more
stress and vulnerable to predation and this may be responsible for imbalance in the sex ratio in
the older age groups.
DISPERSAL: Some organisms do not occupy all of their potential range. The absence of an
organism from a particular area may be due to its failure to reach that particular area and there
can be several factors, physical and biological acting as barriers to the dispersal power of the
organism. When the organisms are transported outside their normal range, they survive,
reproduce and spread. They may form new species in response to changed environmental
conditions. Thus, dispersal is an ecological process affecting distribution and a genetic process
affecting geographic differentiation.
Dispersal is the movement of individuals or their disseminules (seeds, spores, larvae etc.) into
or out of the population. Most of the organisms disperse at some stage of their life cycle and
these movements are essential for their survival. Many factors like lack of food, shelter and
increased inbreeding may force the organisms to disperse.
Apart from natality and mortality, dispersal helps population in shaping population growth
forms. Usually some individuals or their reproductive parts are constantly entering or leaving
the population but it has little effect on the population. However, larger changes will affect the
population. Dispersal is influenced by barriers and by the inherent power of movement of
individuals.
Dispersal acts as an important agent in colonization of new areas and establishing equilibrium
diversity; it is an important component of gene flow and leads to the formation of new species.
Mac Arthur and Wilson (1967) has described three types of dispersal in animals:
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Dispersal of small organisms and propagules takes an exponential form as density decreases by
a constant amount of equal multiples of distance from the source.
Normally distributed pattern observed in large active animals.
Uniform pattern also called as set distance dispersal e.g. birds flying from one island to another
island. Honeybees may avoid food near the hive in favour of food at greater distances.
In animal population, dispersal takes the following different forms:
Emigration is one-way outward movement from a population. Emigration can be due to
overcrowding, shortage of resources or some unfavourable social or physical factors. People
leave their hometown in search of better opportunities and do not return to the place of their
origin.
Immigration is one-way inward movement of organisms into an area, which is useful for the
survival and well being of the organisms. People leave India for better job prospects and living
condition in U.S.A. It is an example where people are emigrating from India and immigrating to
U.S.A.
Migration is periodic departure and return of organisms from and to the population. Migratory
movements of animals generally fall into three categories.
Migratory movements may be daily as observed in oceanic zooplankton. The crustaceans
(Cladocera and Copepoda) undergo vertical migration in response to changes in light intensity.
Because of heating of water on the surface during daytime, they move to deeper water and as
the temperature decreases at night, they come to the surface of water. Bats travel to feeding
grounds at night and return to roosting places at dawn. Migration in earthworm is seasonal. It
undergoes vertical migration spending winter in deeper soil and appears on the surface of soil in
spring and summer. The Kashmir Stag undergoes vertical migration in the Dachigam sanctuary;
in winter, it comes to the valley and in summer, it ascends to the higher elevations of the
mountainous region. The most interesting of all migrations is the annual spring return and fall
departure of the migratory birds. Siberian Crane is known to make annual visits to Indian
subcontinent in the months of November and December, particularly to Keola Deo National
Park, Bharatpur. Migrations are also known to occur in Mule deer, elk, caribou and whales
either for food or reproduction.
Migrations may involve one return trip by the organisms e.g. in some species of Pacific salmon,
the young hatch and grow in headwaters of coastal streams and rivers. The young move
downstream into the open sea, where they reach sexual maturity. Once they attain maturity,
they return to their home streams to spawn and then die.
Third type of migration is characterized by the monarch butterfly. This is an unusual type of
migration, as the adult migrants never return to their home grounds of north in summer from the
wintering grounds of south; however, their offsprings return to their home ground. Some
leafhoppers, the harlequin bug and the milkweed bug undertake similar but less extensive
migrations
Nomadism is the random movement of individuals in search of food and shelter without
definitely returning to the place of origin. Some tribes in Rajasthan state of India are nomads.
The affect of dispersal on a population depends upon its growth form and its rate of dispersal. A
well-stocked and balanced population with respect to limiting environmental factors is not
affected by emigration and immigration, as it is compensated by natality and mortality.
However, if the population is below or above the carrying capacity level, population is affected
e.g. immigration may speed up population growth or in case of extreme reduction prevent
extinction. Mass dispersal can change the population in other ways e.g. large number of bluegill
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fingerlings introduced into a pond, where its population has reached carrying capacity, results in
decreased growth and small average size of the fish. So the biomass may remain unchanged but
the individual size is so reduced that fishing becomes poor.
For mobile animals, dispersal is active but sessile organisms depend on other agencies for their
dispersal. They disperse by different mechanisms and these include dispersal by wind, water,
coats of animals and feathers of birds. Some organisms are dispersed through the digestive
system of the animals. Wind helps in the dispersal of spiders, larvae of insects and cysts of
brine shrimp. Running water of streams carry the larval forms and other organisms to their
suitable microhabitat and help in their dispersal to far off places.
DISPERSION: It refers to internal distributional pattern of organisms within a population.
The individuals in a population are distributed in space and time. Accordingly, the distribution
is called as spatial dispersion and temporal dispersion. Spatial dispersion can be divided into
three broad categories (Fig. 1.4).
Random distribution is rare as it occurs in uniform environment, resources are equally
available and there is no tendency of aggregation. Spiders in the forest floor and the clam
(Mulinia lateralis) of the intertidal mudflats of the northeastern coast of N. America show
random distribution.
Uniform Distribution occurs when competition between individuals is severe and the
individuals are more evenly placed. Severe competition for light among forest plants result in
their uniform distribution. Autotoxicity among plants of arid region also result in uniform
distribution of plants in these areas.
Clumping is the most common pattern of distribution and results in the aggregation of
individuals. This distribution is in response to differences in the habitat, environment,
reproductive pattern and social behaviour and it results in random clumped, uniform clumped
and aggregated clumped distribution pattern. Human population show clumped distribution due
to their social behaviour, economic condition and geographic factors. Those populations, which
show aggregated pattern of dispersion, suffer from competition for food and space but this is
balanced by the group survival value of the individuals. Individuals in groups often experience
lower mortality during unfavourable periods or during attack by organisms then do isolated
individuals, because the surface area exposed to the environment is less in proportion to the
mass and also the group may be able to modify the microclimate to some extent. The degree of
aggregation and over all density that result in optimum population growth and survival varies
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with the species and conditions. Therefore, undercrowding (lack of aggregation) and
overcrowding may be limiting to the population. This is Allee’s Principle.
Group survival value resulting from aggregation is an important characteristic. Allee found that
a group of fishes could withstand a given dose of poison in water much better than isolated
individuals, Also isolated individuals were more resistant to poison when placed in water
formerly occupied by a group of fishes than when placed in water not so biologically
conditioned. In the earlier case, mucous and other secretions aided in counteracting the poison,
indicating some group action type of mechanism. A hive or a cluster of bees can retain and
generate enough heat in the mass for the survival of all the individuals at a temperature low
enough to kill all the bees if each were isolated. Allee observed that these types of primitive
cooperation are the beginning of social organization, which shows varying degree of
development in the animal kingdom culminating in the group behaviour of human beings. It is
relevant to the human conditions. Aggregation into cities and urban dwellings is beneficial to
humans but only up to a certain point. Since the optimum size of the cities has not yet been
objectively determined, the cities should reduce their population when the costs exceed their
benefits. Ecologically it is a mistake to maintain a city that is too large for its support.
A special type of aggregation is called refuging. It is an aggregation of a large socially
organized group of animals settling in a favourable place from which they disperse and return
regularly to satisfy their needs like food and material comforts. Human populations employ this
strategy. It is a common phenomenon in developing and under developed countries.
Temporal dispersion: It can be circadian related to daily change in light and dark as observed
in the activities of some animal populations e.g. nectar feeding insects and oceanic plankton.
Temporal dispersion may be related to seasons, lunar cycles and tidal cycles, e.g. certain
activities of marine animals are regulated by periods of moon and by the intensity of tides,
whereas in terrestrial animals, photoperiodism play an important role in regulating their
activities.
INNATE CAPACITY FOR INCREASE IN NUMBERS: It is also called intrinsic rate of
natural increase or Malthusian parameter. It is a statistical characteristic of population. Any
population in an environment has a mean survival rate, mean growth rate and mean birth rate
and the values of these are determined by the environment and certain innate quality of the
organisms themselves. But this innate quality of the organisms is not constant and its
expression can be measured only under specified conditions.
When the environment is favourable, the population’s capacity for increase is positive and
when the environment is unfavourable the population’s capacity for increase is negative.
Therefore, a population cannot go on increasing forever. In nature, we observe an actual rate of
increase (r), which varies from +ve to –ve in response to changes within the population in age
distribution, social structure, genetic composition and changes in environmental factors. The
difference between instantaneous specific natality rate (b) and the instantaneous death rate (d) is
represented by r. It can be expressed as
r=b–d
In the laboratory, we can eliminate unfavourable changes in weather, provide ideal food and
eliminate predators and diseases and under these artificial condition, we can observe the innate
capacity for increase (rm). Chapman (1928) proposed the term biotic potential for rm and
described it as the inherent property of the organism to reproduce, to survive and to increase in
numbers. The rm is defined as “the maximum rate of increase attained at any particular
14
combination of temperature, humidity, quality of food and so on, when the quantity of food,
space and other animals of the same species are kept to an optimum and other species are
entirely excluded from the experiment”. The difference between the maximum value of rm or
biotic potential and the rate of increase that occurs in actual or field conditions is a measure of
environmental resistance. The environmental resistance is defined as the sum total of
environmental limiting factors that prevent biotic potential from being realized.
Though the innate capacity for increase is arbitrarily defined with regard to a specific laboratory
situation, still it is important as it gives us a model with which we can compare the actual
observed rate of increase in nature. Thus innate capacity for increase in numbers cannot be
expressed quantitatively except for a particular environment.
Any component of the environment such as temperature, humidity or rainfall might affect the
birth and death rates and hence the rm. An example of the effect of environment on the innate
capacity for increase was shown by Birch (1953) in his work on Calandra oryzae, a beetle pest
that lives on stored grain. It was found that the rm varied with the moisture content and
temperature of the wheat clearly implying that to prevent loss of wheat due to pest damage, it
should be stored in cool and dry conditions.
The rm does not reflect on the rareness or commonness of the species. Species with a high
rmvalue are not always common and a species with a low rm are not always rare (Slobodkin,
1961). Some species such as buffalo in North America, the elephant in Central Africa and the
periodical cicadas are quite common and yet have a low rm value. Many parasites and
invertebrates with a high rm value are nevertheless quite rare. Generally, three factors are
responsible for an increase in the rm value:
•
reductions in age at first reproduction,
•
increase in litter size and
•
increase in the number of litters.
In many cases, quite noticeable effects are obtained by changing the age at first reproduction.
Cole (1954) showed how changes in age at first reproduction in humans could affect the innate
capacity for increase in numbers. He observed that if all the women were 20 at the time of first
reproduction, 3.0 children would provide an rm=0.02; if the first birth is delayed until the of 30,
3.5 children are required to provide rm=0.02. Similarly, to get an rm= 0.04 women can start
reproduction at the age of 13 and produce 3.5 children or they can start reproduction at the age
of 25years and have 6.0 children.
Therefore, age at first reproduction is obviously very important in determining the growth of
human populations.
In nature, it is difficult to find populations with stable age distribution or with constant age
specific rates of mortality and fertility and therefore, the actual rate of increase observed in
nature is more complex than the theoretical rm. The importance of rm is that we can use it as a
model to compare with the actual rates, of increase observed in nature.
HUMAN POPULATION GROWTH
An insight into the human history indicates that human populations have not been very large in
comparison to other species. For thousands of years, the population growth has been very slow.
Archaeological evidence and historical description suggest that only about 300 million people
were living at the time of Christ (Pop. Ref. Bureau, Inc. Washington, D.C.). The population was
limited by high mortality and even in Great Civilization of Egypt, Greece and Rome;
expectation of life did not exceed 30 years. The checks were by disease, famine and wars. 25%
of the adult population of Europe died in the epidemics of bubonic plague in the 14th century.
15
The diseases like malaria and yellow fever severely limited the abundance and distribution of
people in tropical countries.
Human populations showed rapid growth only after A.D. 1600. This was mainly because of
rapid growth in the field of agriculture, industry, commerce and power. Better medical facilities
and hygiene also played an important role in population growth. As a result of developmental
activities around the world, human population is now experiencing exponential or J- shaped
pattern of growth. The population reached one billion mark in 1804 but it took about 150 years
to reach 3 billion mark in 1960. In 1999, the population reached 6 billion mark and it took only
12 years to add 6th billion to the population from 1987 to 1999. In 2003, the world population
stood at 6.3 billion mark and at the current rate, the world population of 6.3 billion is projected
to reach 7- 14 billion mark sometimes in this century (Fig. 1.5).
Apart from birth and death, the size of a population is affected by immigration and emigration
as some individuals are constantly entering or leaving the population, therefore, the population
projection for the future can be had from the equation given below:
Nfuture = Npresent + (B - D)+ (I – E)
Where, Nfuture is the predicted population size at a given time in the future and Npresent is the
present population size; B is birth rate, D is death rate and, I and E are immigration and
emigration, respectively.
The human population is increasing at a rate, which outstrips the capacity of social and physical
resources. Every second, on an average, four or five children are born somewhere on the earth
and at the same time two people die, and it amounts to a net gain of approximately 2.5 more
humans per second in the world population. We became the most numerous species on this
planet when we reached the 6.3 billion numbers in 2003. Population size changes due to births,
deaths and migration. Birth rates and death rates are decreasing worldwide but death rates have
fallen more sharply than birth rates. The exponential growth rate has not disappeared but
occurring at a slower rate. India reached a population of 1.1 billion in 2003 and if current
growth rate continues, India will have 1.63 billion people in 2050 and will overtake China as
the most populous country but it will be a great problem for India to provide food, housing,
education, employment and health care to all its people. Approximately, one fourth of its
population may be living in very poor conditions. The other nations expected to experience
most of the increase in population growth are Pakistan, Nigeria, Bangladesh and Indonesia. It is
not surprising to note that toady, India and China together make 38% of the world’ population.
Population pressures certainly contribute to international tension. There is always tension on the
Indian border with Pakistan as well as with China.
There are conflicting views regarding the utilization of resources and increase in human
population.
One view is that overpopulation will lead to resource depletion and environmental degradation
causing the life support system to collapse. There will be increasing pressure for birth control
programmes and to reduce the fertility rates.
The second view is that human ingenuity, technology and enterprise can extend the world’s
carrying capacity, enabling the people to overcome any problem encountered.
16
Some people believe that current shortages are artificial and creation of few rich people because
of their tendency of greed, wastefulness and oppression. The root cause of environmental
degradation seems to be inequitable distribution of wealth and power.
Demographically: The world can be divided into two contrasting groups. One group is that
part of the world which has less developed countries of Africa, Asia and Latin America
representing 80% of the world’s population. Here, the people are poor, young and population
growth rate is very high; and 90% of the projected world’s population growth is expected here.
In Oman and Palestine, population growth rate is very high and the doubling time is only 18
years. The other group is of richer countries of N. America, Western Europe, Japan and
Australia. This part of the world is wealthy, old and populations do not show sign of growth.
While U.S.A. and Canada may have nearly stable population, if they completely stop
immigrations, countries like Italy, Hungary, Germany and Japan have negative growth rates
(Fig. 1.6). Germany has the lowest birth rate in the Europe, with 8.5 births per 1000 inhabitants
and if this declining trend in population continues then Germany would die out entirely by
2300. The world seems to be divided into geriatric and paediatric societies. In Europe the
number of over 50s outweighs the number of under 15s, with the over 85s the fastest growing
demographic group. In Africa and other and other developing countries, it is just the other way
round. In Russia, population is declining by about one million people per year as it has very
high death rates and very low birth rates and the population seems to be completely
demoralized.
17
18
For progress and welfare of the people in less developed countries, population growth has to be
controlled and an attempt should be made to attain Zero Population Growth (ZPG). However,
it takes several generations of replacement level fertility to reach ZPG. Replacement level
fertility is the number of children a couple must bear to replace themselves. In Europe, 2.1 is
considered to be the population replacement level while for Germany, it is 1.37, Spain, 1.32,
Greece, 1.29 and Italy, 1.33.Thus fast decling birth rate is a headache for the European
countries (H. T, June 6,2006). Fertility is to be differentiated from fecundity. Fecundity is the
physical ability to reproduce; fertility describes the actual production of offsprings. Therefore, a
person without children may be fecund but not fertile. Fertility rate (the number of children
born to an average woman in a population during the entire reproductive period) has declined
considerably in every part of the world in the last 50 years. The greatest fertility reduction has
been in Southeast Asia. Bangladesh has reduced its fertility rate from 6.9 in 1980 to 3.1 children
per woman in 1978. In China fertility rate has reduced from 6 in 1970 to 1.8 in 1990 and if
fertility decline follows a pattern of Bangladesh and China, the population of the world may
show a decline by the end of 21st century.
Global transformation in human health in 20th century led to an increase in life expectancy,
which can be defined as the average age that a new born infant can expect to attain in any given
society. For example in 1900 the average Indian could live less then 23 years, the life
expectancy has increased to nearly three times in 2000. The increase in life expectancy is
attributed to better nutrition, improved sanitary condition and medical facilities.
DEMOGRAPHIC TRANSITION: Demographic transition is based on interpretation of
American demographer Warren Thompson (1929). He observed transition in birth and death
rates in industrialized societies in the past 200 years. Demographer, Frank Notestein (1945) also
observed a typical pattern of falling death rates and birth rates due to improved living
conditions accompanied by economic development. He called this pattern demographic
transition from high birth and death rates to lower birth and death rates. The general model of
demographic transition shown in Figure1.7 is used to explain connection between population
growth and economic development. The transition takes place in four stages:
1. Preindustrial phase: A balance between birth and death rates till the late 18th century
characterizes it. The birth and death rates are high around 30 to 50 per thousand and
population growth is slow. Sometimes, it is also called as stationary stage of population
growth (“high” birth and death rates, “stationary” rate and “stationary” total population
numbers). High death rates were due to disease, food shortage and poor living
conditions. High birth rates could have been due to factors associated with high fertility,
seen even today in less developed countries.
2. Transitional stage: There is increase in population due to decline in death rate but birth
rate remains high. The decline in death rate is due to improvement in food supply, high
agricultural yields and improvement in public health systems like water supply, sewage,
food handling and personal hygiene as well as female literacy. Due to decline in death
rate, rapid increase in population growth occurs and the gap between birth and death
become wider. There is a change in the age structure of the population as deaths are
confined to 5-10 years ages. The decline in death rate resulted in increased survival of
children and the age structure of the population became expanding type. The population
increase may be 2.5 to 3.0% per year.
3. Industrial stage: It is characterized by a fall in birth rates, which eventually approaches
the death rates as industrialization and modernization become widespread. Population
growth continues but at a slower rate depending on the economic conditions. In rural
areas people realized the need not to have many children for comfortable old age.
19
Increased female literacy and employment helped females in influencing childbearing
decisions. Improved contraceptive technologies helped in the second half of the 20th
century. Towards the end of industrial stage, the fertility level falls close to replacement
levels but population growth continues on account of population momentum. Most of
the developed countries are in the third stage of transition and a few developing
countries are entering this stage.
4. Postindustrial stage: It is characterized by stability of the population. The decline in
birth rates continues further till it equals the death rate and thus reaching the zero
population growth. The birthrate falls below the death rate and the total population size
decline gradually till the zero population growth rate is attained. The population age
structure becomes older. It is estimated that 38 countries of Europe containing about
13% of the world population have entered this stage.
In most of the developing countries today, death rates have fallen much more than birth rates
and these countries are still in the transitional stage. The population growth rate is high and
economic development is not fully attained. Some economists are of the view that these
developing countries will make the demographic transition over the next few decades without
increased family welfare efforts.
Many workers are of the opinion that:
Rapid population growth in developing countries will out strip economic growth and degrade
local life support system. These countries may be trapped in demographic transitional stage, as
in Africa, where some of the countries are affected by HIV/ Aids epidemic and are falling back
to the preindustrial phase of demographic transition as the death rate rises.
The factors that allowed developing countries to develop are not available to many of the
developing countries, as they could not have enough workers to produce technically advanced
products needed to compete in the global economy. They lack the capital and the resources
needed for economic development.
Since 1980, the developing countries have experienced a drop in economic assistance from
developed countries and a rise in their debt to such countries will slow down the pace of
development.
On an optimistic note, some of the factors that help in stabilizing population growth are as
follows:
Social reforms coupled with growing prosperity leads to reduced desire for large families.
Modern technology can be made use of in making the developing countries advanced much
earlier.
Developing countries can learn from the mistakes of more developed countries and devise
strategies to attain stability at the earliest.
Modern communications have helped in improving the living standard of the people by
exposing them to the developments in the world.
Many people feel that social justice is the key to successful demographic transitions. The world
has enough resources for everyone but inequitable social and economic system leads to
maldistribution of these resources. It is believed that unequal distribution of resources rather
than lack of them is the root cause of poverty, hunger, violence, overpopulation and
environmental deterioration.
20
21
POPULATION GROWTH IN INDIA: India is a multireligious and multilingual nation and
Indian people follow different cultures. It is a developing country. On one side, it is engaged in
developmental activities, while on the other side, it is struggling with the ways and means of
controlling its rapidly increasing population. The first family programme of the world was
launched in India in 1952 and at that time its population was 400 million. In 2003, after 51
years India’s population was 1.1 billion and it was the world’s second most populous country.
The population and sex ratio of India from 1901 to 2001 on the basis of census taken every ten
years is shown in (Table 1.2). The population density of India was 324 people per square km.
West Bengal had the highest population density of 903 people per sq km and Bihar was the
second among states. However, Delhi had the highest density of 9340 people per sq km and
Chandigarh was the second with a population density of 7900 people per sq km. The sex ratio is
unfavourable to females. It was 933 females/1000 males in 2001. India has 2.4% of the world’s
surface area but sustains 16.7% of the world population. The National Commission on
Population was constituted under the Chairmanship of the Prime Minister to provide over all
guidance for population stabilization by promoting synergy between demographic, educational,
environmental and developmental programmes. The high fertility states in India are Uttar
Pradesh, Bihar, Rajasthan, Madhya Pradesh and Orissa. India is projected to have a larger
population than China by 2050, even if China relaxes their one child policy.
Though the Indian Government is doing its best to improve the living standard of its everincreasing population by providing employment, housing, food and education but the situation
may worsen if the population continues to grow rapidly. By global standards, Indian people are
poor and nearly half of its labour force is unemployed or finds occasional work. The only good
news is that India is currently self sufficient in food grain production but still 40% of its
population and 53% of its children suffer from malnutrition, mainly because of poverty. About
half of the country’s cropland is degraded as a result of soil erosion, water logging, salination,
over grazing and deforestation. Also 70% of India’s water is polluted and sanitation services are
often inadequate. The results of family welfare programmes have not been very encouraging,
may be because of poor planning, bureaucratic inefficiency, the low status of women and lack
of administrative and financial support. The government has propagated the advantages of small
families but still Indian women have on an average 3.1 children. The poor people believe that
they need many children to do work and care for their old age. Generally, there is a strong
preference for male children and couples keep on having children until they have a boy. Thus in
spite of the awareness of the family welfare programmes in majority of the population, about
half of the people may be using some methods of birth control.
The different methods of population control include:
Family welfare programmes which provide maximum freedom of choice to each couple to plan
the number and spacing of their children and does necessarily mean having fewer children.
Socioeconomic measures which include large scale educational programmes through schools
and other communication media to acquaint people with the advantages of small families to
themselves and to the society The tax laws can be adjusted to favour single people, working
wives and small families. There can be an increase in marriage fees, tax on luxury goods and
baby toys, removal of family allowances and limitation of educational benefits to two children
per family wherever they exist. Other measures include late marriage and childlessness. A
special kind of social security pension could be provided for aging adults who have no children
to support them in the old age. Social pressure on both men and women to marry and have
children must be removed and alternative life style should be open to single people and
childless couples.
22
Birth control methods mean any method to reduce births. Modern medicines give more options
for controlling fertility than were available to our ancestors. The methods of birth control
which prevent the meeting of sperm and ovum are as follows:
Avoidance of sex during fertile periods e.g. celibacy, using changes in body temperature or
cervical mucous to judge when ovulation occurs.
Mechanical barriers that prevent contact between sperm and egg e.g. condoms, spermicides,
diaphragms, cervical caps and vaginal sponges.
Surgical methods that prevent release of sperms or eggs e.g. tubal ligations in females and
vasectomy in males.
Chemicals that prevent maturation or release of sperms or eggs or embryo implantation in the
uterus e.g. progesterone or estrogen and progesterone for females and for males it is gossypol.
Physical barriers to implantation e.g. intrauterine devices.
Abortion or termination of pregnancy.
Some of the methods that may not be very successful with the population include compulsory
sterilization of women after 2 – 3 children or compulsory implantation of steroid capsule at
puberty, which can be removed for child bearing with official permission. Technically
impossible but theoretically feasible is that, fertility reducing agents can be added to staple
food, water, etc.
Table 1.2- Population and Sex Ratio in India 1901 -2001
Census Year
Population
Millions
in Sex Ratio
Females / 1000
males
1901
23,83,96,327
972
1911
25,20,93,390
964
1921
25,13,21,213
955
1931
27,89,77,238
950
1941
31,86,60,580
945
1951
36,10,88,090
946
1961
42,92,34,771
941
1971
54,81,59,652
930
1981
68,33,29,097
934
1991
84,64,21,039
926
2001
1,02,87,37,436
933
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POPULATION GROWTH
Populations are not static entities and all the organisms have the capacity for substantial
population growth. The potential for reproduction is always greater than achieved e.g. female
mouse has the potential to ovulate 10-12 egg cells every five days but only a small % age can
become fertilized and develop into living youngs. Fertilization at normal rates would produce
3000 progeny every year, because gestation period is 21 days and weaning for 21 days and they
mature sexually in 21 days; so at 42 days age, they are ready to breed and also the female has a
post partum heat i.e. she comes into heat or estrous within 24 hours after the birth of her litter
and ovulates a new set of eggs and can mate again. So it can support gestation and lactation at
the same time. A human female produces 300-400 ova in the course of her lifetime. If
conception occurs at maximum rate, a female can produce one young every / 12-15 months or
20-25 youngs in the course of her life time, this is still 8-10 times higher reproductive potential
then the average family size in most countries.
Thomas Malthus (1798) observed that populations increase geometrically or exponentially
where as their food supplies and means of subsistence increase arithmetically. In exponential
increase, a number beginning with the base number 2 and an exponent of 2 would be
represented by the series 2, 4, 16, 256 etc. and so on; in geometric increase, it is a series of
numbers having a common ratio such as 2 ,4, 8,16, 32, 64, etc where the succeeding number is
a multiple of the former; but in arithmetic increase, it is a series of number having a common
difference such as 2,4,6,8,10,12 etc in which the number differs from others by the same
quantity.
Growth rates: Populations are not fixed entities and with time they show change in age
structure, density and growth forms etc. Demographers now a days seem to be more interested
in studying the pattern and rate of change of populations. The rate is usually obtained by
dividing the change in the entity by the time period during which the change has occurred. The
letter N denotes the number of organisms and writing the symbol ∆ before the number of
organisms denotes any change in number
Therefore,
N
= Number of organisms
∆N
= Change in the number of organisms
∆t
= Time period during which the change has occurred
∆ N/ ∆ t= Growth rate
Growth rate is defined as the rate of change in the number of organisms / time.
∆ N/ N ∆ t= Specific growth rate
Specific growth rate is defined as the average rate of change in the number of organisms /time
/ unit of the population or the organisms present initially.
Instantaneous growth rate: When we are considering the instantaneous rate at a particular
time i.e. when the rate of change ∆ t approaches zero, the letter d replaces ∆ and the equation
can be written as follows:
d N/ d t = The rate of change in the number of organisms/ time at a particular instant.
d N / N d t = The rate of change in the number of organisms / time / unit of population at a
particular instant.
24
GROWTH FORMS: Populations have characteristic patterns of increase called population
growth forms. The two basic patterns based on the shapes of arithmetic plots of growth curves
are the J- shaped and S-shaped or sigmoid growth form. When a few individuals are introduced
into a suitable but unoccupied area with an unlimited environment, its population will tend to
increase geometrically. Assuming that there is no migration and no mortality then birth rate
alone will be responsible for change in the number of individuals. But growth of a population is
limited by death, so it should also be accounted for.
The unrestricted increase in population is called exponential growth because its rate can be
expressed as a constant fraction or exponent by which the existing population is multiplying.
Assume that in a short interval of time dt, an individual has the probability b dt of giving rise to
another individual. In the same time interval, it has the probability d dt of dying. If these are
instantaneous rates of birth and death, the instantaneous rate of population growth / capita will
be:
Instantaneous rate of population growth
=r
And population increase = dN/dt = rN
dN/dt =(b – d) N with a definite limit on N
= b- d
This is the differential equation for exponential growth, where
N= population size
t= time
b and d = instantaneous rates of birth and death, respectively
r = per capita rate of population growth
The value of r may be 1.5 if each individual produces 1.5 times its own number in each time
step and the population is expanding, if r is less then 1,then the population is shrinking and if r
is exactly 1, then there is no change and dN / dt = 0.
The differential equation states that the rate of increase dN/ dt is directly proportional to
population size and rate of growth of population. The growth rate expresses growth or decline
per individual.
A more useful equation for calculating exponential growth is the integrated form
Nt = N oert
Where e = the base of natural logarithms 2.71828. (a constant)
No = number at time zero
Nt = number at time t
r = the rate of increase
t = the unit of time
The equation for population growth is also referred to as biotic potential, the potential of a
population to grow if nothing were limiting to its expression. In reality, many factors prevent
most populations from growing at their biotic potential.
A graph of exponential population growth is described as a J- shaped curve (Fig. 1.8a) because
of its shape. As is evident from the graph the number of individuals added to the population at
the beginning of the exponential curve will be rather small; but within a very short time the
25
numbers begin to increase quickly because a fixed percentage becomes a much larger amount
as the population increases in a compound interest fashion. A J-shaped curve is found in many
organisms introduced into a new and unlimited environment e.g. when 4 males and 21 females
of reindeer were introduced on St. Paul, one of the Pribilof islands in Alaska in 1910, the
reindeer population increased to 2200 in only 30 years and exhibited exponential growth,
overgrazed the habitat and it crashed also in an exponential manner to only eight animals in
1950. Such curves occur in organisms with rapid growth rate, exceed the available resources
and then crash. Where as 3 males and 12 females introduced on St. George Island reached a low
number of 222 reindeer in 1922 and then reduced to a small herd of about 60 animals in 1922.
The difference in bahaviour of two populations may be due to illegal hunting on St. George
Island (Fig.1.9).
26
27
In the real world, however, there are limits to growth. We call the maximum number of
individuals of any species that can be supported by a particular ecosystem on a sustainable basis
its carrying capacity. At this level the population theoretically is in equilibrium with its
environment. When a population overshoots, or surpasses the carrying capacity of its
environment death rate will begin to surpass birth rate. The growth curve becomes negative and
the population decreases, this dieback of population is called population crash. Populations
may go through repeated oscillating cycles of population growth and decline (Fig. 1.8b) and
they may be regular if they depend on a few simple factors, e.g. seasonal light and temperature
dependent blooms of algae in lake. Nicholson (1954) described these fluctuations in population
as density triggered. They may be irregular if they depend on complex environmental and
biotic relationship that control cycles, such as the outbreak of migratory locusts in the desert.
Sometimes, predator and prey populations oscillate in a sort of synchrony with each other (Fig.
1.13). The numbers of Canadian lynx fluctuate on about a ten-year cycle that is similar to the
population peaks of snowshoe hares. When the hare population is high and food is in plenty,
lynx reproduction is very successful, and lynx population grows rapidly. Eventually, declining
food supplies limit hare populations. For a while the lynx populations continue to grow because
starving hares are easier to catch then healthy ones. As hares become more scare, so do the
lynx. When hares are at their lowest levels, food supplies recover and population of both
predator and prey increases. This predator-prey oscillation is known as the Lotka-Volterra
model, after the scientist who described it mathematically.
But populations do not show continuous geometric increase. Many species are regulated by
both internal and external factors so that they come into equilibrium with their environmental
resources and maintain relatively stable population size. These species may grow exponentially
when resources are unlimited, but their growth slows as they approach the carrying capacity of
the environment. This pattern is called logistic growth because of its constantly changing rate.
The growth curve described by such a population is S-shaped or sigmoid curve (for the Greek
letter sigma) (Fig. 1.10a). In the sigmoid form of population, usually the population increases
slowly at first (+ve acceleration phase), then more rapidly (perhaps approaching the logarithmic
phase) but soon it slows down gradually as the environmental resistance increases % age wise (ve acceleration phase or retardation phase), until a more or less equilibrium level is reached and
the population is maintained at this level. The factors that tend to reduce population growth
rates are called environmental resistance. The resistance becomes larger and the rate of logistic
growth becomes smaller as the population approaches the carrying capacity of the environment.
The point in the logistic growth curve where population growth is maximal is K/2 and is known
inflection point. So for a carrying capacity of 100, the inflection point will be 50. From this
point onwards, population growth slows down. It results due to increased detrimental factors as
the density of the population increases. Nicholson (1954) described this type of growth as
density conditioned. The S- shaped curve differs from the geometric curve in two ways:
a. It has an upper asymptote i.e. the curve does not exceed a certain maximal limit
supported by available resources.
b. It approaches this asymptote smoothly and not abruptly.
28
Mathematically, the growth pattern is described by the following equation, which adds a term
for carrying capacity (K) to the biotic potential growth equation:
r
K
= rN-
= rN( 1 -
N2
N
)
K
This equation states that:
Realized rate
of increase of
population
per unit time
=
Potential rate
of population
growth
per capita
x
Population
size
x
Unutilized
opportunity for
population
growth
This is the differential form of the logistic curve. Pierre-Francois Verhulst first suggested this
curve to describe the growth of human populations in 1838. The same equation was
independently derived by Raymond Pearl and I.J. Reed (1930) of John Hopkins University, for
the growth of the population of the United States. The integral form of the logistic equation can
be written as follows:
Nt = K / 1 + ea-rt
In the equation
N = population size
Nt = population size at time t
t = time,
K = maximum value of N,
e = 2.71828 (base of natural logarithms)
a = a constant of integration defining the position of the curve relative to
the origin
r = rate of population growth per capita
As we reach the upper limit of population, it stops growing because (K – N)/ K becomes zero.
The term (1- N / K) in the logistic equation represents the relationship between N at any given
time step and K, the number of individuals the environment can support. If N is less then K, say
100 compared to 120, then (I- N/ K) is a positive number (1-100/ 120 = 0.17) and population
growth, dN/dt is slow but positive, but if N = 150 and K = 120 then (1- N/K) is (1-150/120 = 0.25) and the growth rate is negative. The logistic growth model thus describes a population
that decreases if its numbers exceed the carrying capacity.
According to the logistic equation the population functions as a system regulated by positive
and negative feedback mechanisms and as N approaches K the population theoretically
responds instantaneously as density dependent reactions set in. But usually the feedbacks do not
work as smoothly in nature as suggested by the equation. We add a reaction time lag (W), a lag
29
between environmental change and a corresponding change in the rate of population growth to
make the logistic more reliable. The equation can be written as:
dN = rN K − Nt -w
(
)
K
dt
Another factor representing a reproductive time lag (g), a lag between environmental change
and change in the length of gestation or its equalent is also added to the equation which can be
written as follows:
dN = rNt-g K − Nt -w
(
)
K
dt
Time lags result in fluctuations in populations (Fig. 1.10b). The populations may fluctuate
widely without any reference to the equilibrium size. The fluctuations are basically in response
to the extrinsic factors like weather and intrinsic factors inherent in the population affecting the
behaviour of the organisms in the population. Population may fluctuate around the carrying
capacity level, K, oscillating between upper and lower limits.
When we describe the population growth by the logistic curve, it confirms to the following facts
about the population.
1.
2.
3.
4.
The population has a stable age distribution initially.
The density has been measured in appropriate units.
The relationship between density and the rate of increase is linear.
The inhibitory influence of density on the rate of increase operates instantaneously with
out any time lags.
Laboratory examples of the logistic theory:
Gause (1934) studied the growth of Paramecium aurelia and P. caudatum (Fig. 1.11) by
providing a constant environment in a limited space in a glass tube with 5 cc of salt solution of
pH 8 and a constant supply of food in the form of bacteria. The upper asymptote (K) was
around 448/cc for P.aurelia and 128 cc for P. caudatum.
Carlson (1913) grew yeast in laboratory and Pearl (1927) calculated the logistic curve for his
data and the upper asymptote for the yeast was 665 (Fig. 1.12). Logistic growth curves have
also been obtained in Drosophila by Pearl (1927) and the upper asymptote was at 346. Pearl
and Reed (1920) fitted the logistic curve to the census data of population growth of U.S.A. from
1790 to 1910 and projected asymptotic value of 197 millions by the year 2060, but the census
data from 1940 onwards show a geometric increase rather than logistic growth.
Some organisms like insects and parasites persist by depending on a high rate of reproduction
and growth (rN). These organisms are described r- adapted and exhibit j-shaped or Malthusian
growth. Other organisms tend to reproduce more slowly as they approach the carrying capacity
(K) of their environment and they are referred to as K – adapted. They exhibit logistic or dome
shaped growth. Although, some species do not fit into exponential or logistic growth pattern,
still it is useful to contrast the advantages and disadvantages of some organisms at the extreme
of a continuum of growth pattern (Table 1.3). Generally, we should avoid implying intentions in
natural systems; but sometimes it helps us to see the differences in terms of strategies of
adaptation and logic in different modes of reproduction.
30
31
For example a female clam can release up to one million eggs over her lifetime. As the eggs
drift away, the mother clam can neither protect them from predators nor help them find food or
a place to live. So majority of them die before reaching maturity, but a few survive so that the
species will continue. Many marine invertebrates, parasites, insects, rodents, and annual plants
follow this strategy. Predators or external factors generally limit the numbers of R- adapted
populations.
In K-adapted populations, the animals are usually larger, live longer and have fewer natural
predators than the species below them in the ecological hierarchy. Elephants e.g. are not
reproductively mature until they are 18 – 20 years old. During youth and adolescence, a young
elephant is a part of family that cares for it, protects it and teaches it how to behave. A female
elephant conceives once every four or five years, thus an elephant herd does not produce many
babies in a given year. They have few enemies and live up to 60 –70 years; even this low
reproductive rate produces enough elephants to keep the population stable when they are
provided appropriate environmental conditions.
Table 1.3 - Some correlates of r and k selection
Character
r-selection
k-selection
Population size
Mortality
Survivorship curve
variable
high, density independent
concave type
Competition
Life span
Selection
favours
not very competitive
short, less than one year
development is rapid
Have high rm value
Early maturity and many
Small offspring
Little parental care and
Investment in offspring
Niche generalists
Pioneers, colonizers
constant
regular, density dependent
convex and diagonally straight
type
keen competitor
long, more than one year
development is slow
low rm value
late maturity and few large
large individuals
high parental care
and investment in offspring
niche specialists
later stages of succession
Climate
variable and unpredictable
constant and predictable
STATUS OF THE LOGISTIC THEORY
The logistic theory has not found favour with most of the Ecologists. Wilson and Puffer (1933)
did not agree with the concept of the logistic theory. Sang (1950) asserted that only in
exceptional cases the logistic curve would occur in Drosophila culture.
The study of vertebrate populations in natural and confined circumstances has produced
population curves deviating from the typical population growth curves and tending towards
irruptive or Malthusian growth curves. Burk (1973) rejected it, calling it a myth, which is
propagated in textbooks. Andrewartha and Birch (1954) have proposed complete evaluation of
the logistic theory. According to them, it provides an imperfect yet useful description of
population growth of organisms with simple life histories e.g. Paramecium, but for animals
32
with complex life histories (insects and vertebrates), the population usually does not confirm to
the logistic curve. Despite its theoretical limitations, logistic theory still remains a useful tool
for the ecologists. According to Wilson and Puffer (1933), the logistic formula should not be
considered as a fixed law of population growth, permitting extrapolation of the curve for
forecasting purposes. However, some workers feel that still it is a convenient description of
growth in certain well-studied populations.
POPULATION FLUCTUATIONS AND CYCLES
Populations have their carrying capacity for different locations depending upon the prevailing
physical and biological conditions. When the populations complete their growth and ∆N/ ∆t
averages zero for a long time, population density tends to fluctuate above and below the
carrying capacity level and these fluctuations may be large or small, regular or irregular.
Populations show fluctuations because of
•
Delay in realizing the full effects of birth and death rates and
•
Changes in the availability of resources, weather, predation, competition, etc.
However, the fluctuations are more pronounced in organisms with a limited breeding season,
short life cycles and having a tendency of migration. The pattern of fluctuations also varies; it
may be seasonal or annual because of variation in the influence of extrinsic factors like
temperature and rainfall and intrinsic factors like energy availability and diseases. For example,
Davidson and Andrewartha (1948) have observed a seasonal change in the population of adult
thrips living on roses. A change in the abundance of heron (Ardea cinerea) because of harsh
winter season in Great Britain has been observed by Lack (1966). Loery and Nichols (1985) in
northwestern Connecticut, have also observed fluctuations in wintering populations of blackcapped Chickadees.
The nature of fluctuations in a population reflects its resilience. Resilience is the rate at which a
population returns to equilibrium after its disturbance by some factors. Resilience is influenced
by the reproductive rate of the organisms. Small organisms like insects have shorter lives and
die quickly but they also recover quickly as they have explosive growth in an exponential or
geometric fashion and have high resilience. However, animals with large body size like
elephants do not have a high reproductive rate and they take longer time to recover to the
equilibrium level; and thus they have a low resilience.
Population fluctuations that have more regular patterns of increase or decrease in numbers are
called oscillations or cycles. These cycles are observed generally in small mammals like voles
and lemmings and larger carnivores like lynx and foxes. The most common interval between
oscillations is 3-4 years as in lemmings and 9-10 years in lynx and snowshoe hare. Surprisingly
these cyclic fluctuations have been observed in simpler ecosystems only like the boreal forests
and tundra region. Fluctuations in lemmings follow a regular pattern and peaks and troughs of
lemming numbers are regularly spaced about 4 years apart. The 4- year cycle also occurs in
mice and foxes.
The snowshoe hare (Lepus americanus), muskrats (Ondatra zibethica), Canadian lynx (Lynx
canadensis) and some foxes have ten-year cycles. In snowshoe hare and lynx population (Fig.
1.13), the periodicity of a ten-year cycle is determined by the hare – vegetation and predator –
prey interactions. The length of the increase phase depends on
•
The average rate of population growth from low to high density.
•
The average biomass of the woody browse present.
The decrease phase depends on
33
•
The response of the native species of woody browse to overutilization by hares. The
bushes respond to heavy browsing by increasing toxins in the new shoots for two to
three years after an increase in hare population. In the extended period food is in short
supply and keeps the hare population at a low density.
•
The intensity and duration of the predation after initial decline of hare from food
shortages.
There are different theories concerning the occurrence of these cycles. According to one theory
proposed by Cole (1954) and Palmgren (1949) it is not possible to distinguish statistically
cycles from random fluctuations, as the populations exhibit a variety of fluctuations in different
environmental conditions. But the statistical reliability of these fluctuations has been proved in
case of lemmings, and snowshoe hare and lynx populations by May (1976) and Bulmer (1975)
respectively. The main feature of these cycles is the regularity of periods and irregularity of
amplitude.
The other group of biologists including Krebs (1985) and Keith (1974) believe that physical and
biological factors cause these cycles. The different factors involved include food shortages,
aggressive behaviour, predation, malfunction of the endocrine gland and changes in the gene
frequencies of the animals making them less resistance to environmental changes. Thus as a
result of interaction between some of the above factors cyclic fluctuations are caused in the
populations.
POPULATION REGULATION
Populations vary in abundance from place to place depending upon the physical and biological
factors in a particular habitat. The number of organisms is always large in a favourable habitat
and less in a poor habitat. Generally, the carrying capacity in the habitats is limited by a
resource, which is present in the most limiting condition. Population in a particular environment
does not show continuous and indefinite increase in their numbers. The regulation of population
size by certain factors limits the population growth. The position of a population on the r – K
continuum will be close to the optimum of population increase and carrying capacity for that
species in its environment. In nature, two types of factors regulate population. These factors are
density dependent and density independent.
Density dependent influences change as the density of the population varies and the
proportion of the organisms affected changes with density. Birth rate is called density
dependent if it falls as density rises (Fig. 1.14a) and death rate is said to be density dependent if
it increases as the density increases (Fig. 1.14b). Population regulation can occur by
•
Decrease in birth rate or
•
Increase in death rate or
When per capita birthrate equals per capita death rate and the population stops increasing (Fig.
1.14c).
Usually at some low densities there is no interaction and birth rates and death rates are
independent of population size but as the density increases the density dependent effects of
birth and death sets in. Density dependent regulation is a homeostatic process. So as the
population reaches a certain size, some density related effects reduce the rate of growth by
decreasing the birth rate and increasing the death rate. But if the population falls below a certain
level, reverse happens and it results in fluctuations till the population is stabilized.
Density independent influences do not vary as the population changes. So the same number of
organisms is affected at any density. Density independent influences do not regulate population
growth but have considerable impact on changes in population size by affecting the birth and
34
death rates and may even mask the affects of density dependent regulation. For example a harsh
winter may damage the potato crop leading to shortage of the potatoes for the people. The
sufferings of the people are the result of their own density and the shortage of potatoes but
weather (harsh winter) is the main cause of decline in production of potatoes.
It is believed that the number of organisms in a population is determined by an interaction
between density dependent and density independent influences, which may vary among
populations and within the same population. Therefore, it is better to discuss the regulatory
35
mechanisms of the population in terms of influences that are extrinsic or intrinsic to the
population.
Extrinsic influences: These factors affect the population from outside and do not form a part of
the population. The factors that help in population regulation are as follows.
Resource availability: Resources such as food and reproductive sites directly or indirectly
function to regulate population through intraspecific competition. Competition exists when the
resource is in short supply. Nicholson (1954) demonstrated the influence of intraspecific
competition in blowflies (Lucilia cuprina) population (Fig. 1.15). In an experiment, Nicholson
supplied to a culture of blowflies consisting of adults and larvae, a daily quantity of beef liver
for larvae and enough dry sugar and water for the adults. He observed that the number of adults
varied with oscillations. When the population of adults was high, large number of eggs was laid
and the resulting larvae consumed all the food before they were large enough to pupate.
Therefore no adult offspring was produced from the eggs and through natural mortality the
number of adults declined further and few eggs were laid. At a particular stage larval
competition was so much reduced that some of the larvae got enough food to grow and pupate
giving rise to adults. However, because of the delay in the developmental process population
continued decline, reducing the intensity of larval competition and allowed an increasing
number of larvae to survive. Slowly the adult population increased again to a very high level
and the whole process started again. Competition for food resulted in stability in blowflies
population and the time lag involved between the addition of egg laying adults by way of larval
survival, to the decling population resulted in alternate overshoot and undershooting of the
equilibrium position causing an oscillating population density.
A density dependent relationship exists between many herbivores, carnivores and their food
supply. For example, in mule deer and white tailed deer when quality and quantity of food is
high fertility is maximum, mortality is low and the rate of increase is high unless it ia checked
by predation and hunting. With increase in population the food declines and poor nutrition
results in the repression of growth, delayed sexual maturity and lower conception rates.
Many herbivores are food specific. Many insects, for example, will live only on one species of
plant. The abundance of the host plant will affect population size. If the plant population
crashes due to some reasons then the herbivore population will also crash.
Weather: It tends to be irregular and unpredictable. Weather exerts its influence on population
indirectly by affecting the amount of food produced by the producers. In deserts a direct
relationship exists between rainfall and rate of increase in population of certain rodents and
birds. The Kangaroo rat has the capacity to conserve water and survive long periods of aridity.
It becomes reproductively active in January and February due to rich growth of plants as a
result of rain, which provide food, water and vitamins to the pregnant and lactating females. But
if the rainfall is scanty, production of Kangaroo rat is low.
Extremes of temperature, high rainfall or drought, mild winters or very cold spells alter the
ability of individuals to survive or reproduce. Adverse weather also affects rearing of young,
mortality, movement and dispersal of organisms within a population.
Disease and parasites: Parasites act as density dependent regulators, as the virulence and the
rate of spread of infectious diseases increases with the density of the population. Rampant
disease can reduce population in a density dependent manner and the disease may be the
consequence of high production rather then a cause of population decline. Bacteria and virus are
the causal agents of animal diseases. For example, rabies is common in densely populated
mammals. Foxes and dogs are the primary causative agent.
36
Disease may be density independent when it is introduced into a population lacking any
resistance to the disease or when it results from environmental changes not brought about by the
organisms involved. The disease can reduce the population, exterminate it locally or restrict its
distribution.
Predation: It acts as a powerful extrinsic regulatory mechanism. A predator can regulate prey
population if the predator increases or decreases its density or effectiveness as the abundance of
the prey increases or decreases. The interplay between the predator-prey results in a
coevolutionary game between the two. In the process both the species evolve and regulate each
other’s populations. Predation has the regulatory effect especially in ungulates where the
predator is a highly skilled carnivore. Deer, moose and caribou are not known to have intrinsic
population controls. Similarly, plant predators like deer and rabbits have a regulatory effect on
plant population. Sometimes, predation may have adverse affects on population regulation. For
example some animals like waterfowl are vulnerable during the nesting and breeding season.
The predator, Didinium and its prey, Paramecium in an experiment by Gause, exhibit an
efficient predator – prey relationship in regulation of their numbers, however, certain features of
the environment were important for oscillations in the predator – prey relationship.
Human activity: Man exerts one of the greatest density independent influences on population
increase. Wild animals are hunted illegally for hides, meat, fur, feathers, antlers and medicinal
purposes irrespective of their numbers. Human activity is mainly responsible for decline in wild
life populations. Man’s ability to change the environment has benefited some species and
harmed others. The insecticides used to control insects pests, generally cause mortality of the
organisms other then the target species in a density independent manner. They lower fecundity
or the survival of the young, interfere with the calcium metabolism causing eggshell thinning
and loss of embryos. They also interfere with the density-regulated processes by eliminating
predators, parasites and competitors.
Intrinsic influences: It includes factors resulting from the activities of the individuals in the
population.
Crowding: As population density increases, the individuals become stressed and these social
stresses act on the individuals through a physiological feed back involving the pituitary and the
adrenal glands. For example, increasing population of mice kept in the laboratory resulted in the
suppression of somatic growth and curtailment of reproductive functions. Fertility in harp seals
(Phoca groenlandica) is density dependent. The harp seals attain maturity faster at low
population density then at higher densities. Studies on some wild life populations under stress
show that crowding can reduce populations. Examples of inverse relationship between density
and rate of body growth are seen in exothermic vertebrates e.g. Dash and Hota (1980), (Fig.
1.16) observed that frog larvae at high densities grow slower under experimental conditions and
may not be able to metamorphose into adult frogs. It took longer time to reach the minimum
threshold size to metamorphose into frogs of 0.75 g. Tadpoles held at lower densities grew
more rapidly and larger and transformed to an average size of 0.889 g. This intraspecific
competition among larval forms had little effect on population size and also the total biomass in
the experiment under study remained almost unchanged.
Social behaviour: Social behaviour functions in the regulation of animal populations by
limiting the number of individuals in a habitat. The two mechanisms associated with social
behaviour are territoriality and social dominance.
A territory is an area, which is actively defended by an animal by marking boundaries and
challenging the strangers if they approach too closely. Territoriality spaces out individuals and
restrict the number occupying a particular habitat. Territories are usually held because they
37
contain a food resource or a site needed for breeding. To establish territoriality, some resource
must be in short supply, it must be defensible and it must be worth fighting for. Since space is
more defensible then food, aggressive behaviour is directed towards excluding other animals
from the space containing food resource. For example tiger hunts alone and has a very large
territory. Generally the territory of a male tiger will overlap that of one or more females and the
territory is also utilized for breeding. Some territories support whole group of animals like the
meerkats (Suricata suricatta), where a few individuals keep watch for dangers or strangers and
the whole group defend the area if necessary. Many wild animals like deer, tigers, monkeys and
birds maintain a territory, especially during the breeding season.
Social dominance also helps in regulating population in some wild animals and birds. In the
arctic ground squirrel, all the females are allowed to nest but territorial polygamous males drive
excess males from the colony and they exist as nonbreeding floating population. In chickens
also, one dominant male has access to all the females in the group and the surplus males are
only at the periphery of the group. If any of the surplus male tries to mate with the females, it is
immediately driven out of the group and a fight may occur between the dominant male and the
surplus males.
Dispersal: It is a constant phenomenon in a population whether it is dense or sparse but it is
very effective at high population densities. Overcrowding with an associated increase in
aggressive behaviour is a major force in producing dispersal. Social hierarchy and territoriality
can force weak individuals to depart and seek relatively unoccupied area elsewhere and they are
generally the maturing young in the population.
If the population is at its carrying capacity, dispersal has little effect on the population density
but affects the age structure slightly. However emigration die to overpopulation and food
shortage reduce population and affect the age structure and reproductive rate whereas
immigration into a growing population increases the growth rate. Emigration may be density
dependent and density independent to a lesser degree.
Saturation dispersal is density dependent. The individuals mostly juveniles and sub-juveniles
either stay and perish or do not breed. The other alternative is that they have to leave that area.
The mass movements of squirrels (Allen 1962) and muskrat dispersal (Errington 1962) are
examples of saturation dispersal.
Pre-saturation dispersal is density independent and the individuals have a high probability of
settling in a new area. The dispersing individuals can be of any age group or sex and usually
they are in good health. Krebs et. al. (1973) studied the population dynamics of the field voles
(Microtus) and observed that dispersal was most common during the increasing phase of
population fluctuations and least frequent during the decline phase. 55% of the loss of females
could be accounted for by emigration. Young females were very common in the dispersing
population then young males but adults of both the species left the area. For dispersal, the
individuals must be motivated to leave that area and they should also have an available habitat.
Some organisms experience artificial dispersal by man outside the natural genotypic range and
they come into contact with regional genotypes e.g. it happens during restocking game animals
from one region to another region by replenishing the species in the depleted habitats.
Genetic feedback: As the animal population increases in density, quality of the population
deteriorates preventing an indefinite increase. Genetic feedback perhaps operates through
density pressure and genetic change within the population. Large increase in population brought
about by changing environment increases the variability in the population and many inferior
genotypes survive. When conditions become rigorous, these ecological inferior genotypes are
38
eliminated and the population is reduced abruptly and tries to stabilize depending on the
environmental conditions.
39
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http://www.uwmc.uwc.edu/geography/Demotrans/demotran.htm last visited on 30.06.2006. Demography
transition by Keith Montgomery
.
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