Download NotesChapter7

Notes towards Conservation Biology Chapter 7
Introductory/Title slide (1)
Hello. This is Gwen Raitt. I will be presenting this chapter on extinction and
conservation.
The picture shows a black rhinoceros (Diceros bicornis).
Why is extinction a concern for conservation biology?
In chapter 1, it was noted that conservation biology developed from the growing
awareness of the present (sixth) mass extinction (Primack 1998) (see also chapter 6 of the
Biodiversity Course). Four factors form the basis for this concern: firstly, the
unprecedented level of threats to biodiversity; secondly, the escalation (growth) of the
threats to biodiversity caused by human population growth and exacerbated by the
unequal distribution of wealth in the world; thirdly, the observation that the threats to
biodiversity are synergistic (i.e. independent threats may act additively or multiplicatively
to increase the negative impacts on biodiversity) and finally, the realisation that what
harms biodiversity will eventually harm humanity because we depend on biodiversity for
our survival (Primack 1998).
Conservation biology aims to prevent the extinction rate exceeding the speciation rate –
not to eradicate extinction (Cox 1997). Thus, conservation biology focuses on
maintaining/promoting the long term viability of ecosystems and their component species
(Soulé 1985).
Categorising Threats to Biodiversity
Threats to biodiversity fall into two categories: systematic (or deterministic – cause and
effect) threats that are mostly ultimately caused by humans and for which the
management responses are usually clear (threats of this type are covered in chapters 2—5
of this course; see also chapter 5 of the Biodiversity Course) and chance (or stochastic)
threats for which the only possible management responses are to maintain the population
size and to attempt to minimise the impact of chance events (Groombridge 1992, Frankel
et al. 1995, Pullin 2002).
The effects of systematic threats (such as habitat fragmentation) usually include increased
vulnerability to chance threats because the systematic threats reduce the population size
and small populations are particularly vulnerable to chance events (Pullin 2002).
Conservation Focus… Populations
Extinction tends to bring specific species (e.g. the dodo - Raphus cucullatus) or other
taxonomic units (e.g. the dinosaurs – the picture shows a Triceratops skeleton) to mind
(Caughley & Gunn 1996).
While conservation of all levels of biodiversity is important (Frankel et al. 1995), the
species is a pragmatic choice of conservation unit because it is (relatively) easily
identifiable and therefore quantifiable (Caughley & Gunn 1996, Pullin 2002) but the
threats that cause species extinction act at the population/metapopulation level (Barbault
& Sastrapradja 1995) and populations share an evolutionary future. Therefore, the
population/metapopulation is the actual unit of management for species conservation
(Frankel et al. 1995, Caughley & Gunn 1996). Populations are also the means of
conserving genetic diversity in the form of allelic diversity (Frankel et al. 1995).
Reducing the probability of chance extinctions for small populations by minimizing the
impact of chance events is an important part of conservation – both in situ (because
reserves exist as islands in a human landscape (Knight 1999)) and ex situ (Frankel et al.
1995, Pullin 2002).
It is, however, also most important to remember not to focus so intensively on small
population size that no action is taken to reduce the factors that caused the original
population decline – the deterministic threats (Caughley & Gunn 1996, Pullin 2002).
Populations
A population is a group of interacting individuals of a given species living in a specific
geographic area at one time (Miller 2002, Wikipedia Contributors 2006a). Population
size is affected by birth, death and migration (Miller 2002). Births and immigrations add
to the population size while deaths and emigrations reduce the population size (Cox 1997,
Miller 2002). The amount of migration depends on the degree of population isolation
(Groombridge 1992). Population size and survival depend on: the availability of
resources such as food, shelter, clean water and clean air; the amount of suitable habitat
available; the amount of predation/parasitism; the prevalence of disease and finally
social interactions (Barbault & Sastrapradja 1995, Dobson 1996, Cox 1997, Miller 2002).
The picture shows Cape Gannet (Morus capensis) behaviour.
Mechanisms of Chance Extinction in Single Populations
Population extinction is certain if, in the long term, the mortality rate is higher than the
birth rate (Barbault & Sastrapradja 1995) in the absence of migration. If migration is
present, extinction is certain if, in the long term, the combined death and emigration rates
exceed the combined birth and immigration rates (Miller 2002).
Extinction mechanisms act by raising the mortality rate, lowering the birth rate (Barbault
& Sastrapradja 1995, Dobson 1996), lowering the migration rate or any combination of
the three. The mechanisms may be grouped into three categories for single populations
(Barbault & Sastrapradja 1995).
Firstly, chance (stochastic) variation occurs in birth and death rates, affecting the
population size. This is known as demographic uncertainty (or stochasticity). Very small
populations are vulnerable to extinction caused by demographic uncertainty. Decreasing
the population density below a critical threshold results in decreased social interaction
between individuals (termed Allee effects) and hence a decreased birth rate and an
increased mortality rate (Barbault & Sastrapradja 1995, Frankel et al. 1995, Caughley &
Gunn 1996, Dobson 1996, Primack 1998, Pullin 2002).
Secondly, environmental uncertainty reflects the effects of chance changes in the
environment in which the population occurs (Groombridge 1992, Barbault &
Sastrapradja 1995, Frankel et al. 1995, Caughley & Gunn 1996, Dobson 1996, Primack
1998, Pullin 2002). This includes such unpredictable events as ‘natural’ catastrophes
(Begon et al. 1996, Caughley & Gunn 1996, Menges 2000) which may be aggravated or
caused by human behaviour (Brown 2001, Pauchard et al. 2006). The picture is of a
flood in Mozambique – the houses conveniently show that the water is above its normal
level.
Finally, loss of genetic diversity (a form of biodiversity loss) affects the chances of
population extinction (Groombridge 1992, Barbault & Sastrapradja 1995). A potential
impact of the loss of genetic diversity is the reduced fecundity and viability caused by
either inbreeding depression (which may occur in the offspring if closely related
individuals mate) or outbreeding depression (caused by individuals from divergent
populations mating with the result that local adaptations to the environment are lost)
(Barbault & Sastrapradja 1995, Frankel et al. 1995). Another impact is the reduction of
genetic variability in small populations due to genetic drift (changes in allele frequencies)
(Barbault & Sastrapradja 1995, Frankel et al. 1995).
The above mechanisms may interact, compounding the effect on the population
(Groombridge 1992). Population size is critical to survival (Barbault & Sastrapradja
1995).
Metapopulations
A metapopulation is made up of a number of spatially separated, extinction-prone local
populations (or subpopulations) that are linked by migration (Groombridge 1992,
Barbault & Sastrapradja 1995, Wikipedia Contributors 2006b). It may be described as a
‘population of populations’ with two levels of population dynamics: within local
populations and between local populations (Begon et al. 1996, Primack 1998). Plants
tend to occur in metapopulations (Frankel et al. 1995).
Other than the classical metapopulation, the following types are recognised: mainlandisland metapopulations which have at least one large stable population that is not likely to
become extinct which provides immigrants to other habitat fragments that may be more
extinction prone (Barbault & Sastrapradja 1995, Caughley & Gunn 1996, Pullin 2002);
source-sink metapopulations which occur if some populations have a growth rate that
exceeds the capacity of the habitat forcing emigration to other populations which have a
higher mortality rate than birth rate (Groombridge 1992, Barbault & Sastrapradja 1995,
Begon et al. 1996, Caughley & Gunn 1996, Primack 1998) and non-equilibrium
metapopulations which are the result of recent habitat fragmentation and may not survive
as no equilibrium exists between colonisations and extinctions and the development of
such an equilibrium is not guaranteed (Barbault & Sastrapradja 1995).
Metapopulation survival depends on: local population survival (see the slide on
populations (slide 5) for factors required for local population survival), unoccupied
suitable habitat at suitable distances (i.e. within migration distance of occupied habitats)
and sufficient migration for colonisation of unoccupied habitat to occur (Barbault &
Sastrapradja 1995). The picture shows a Jackass Penguin (Spheniscus demersus)
subpopulation (colony).
Mechanisms of Chance Extinction in Metapopulations
Extinction of a metapopulation is certain if, in the long term, the local population
extinction rate exceeds the rate at which new populations are established (Barbault &
Sastrapradja 1995, Pullin 2002). Local population extinction mechanisms are those of
single populations. The mechanisms acting at the metapopulation level may be grouped
into two categories (Barbault & Sastrapradja 1995).
Colonisation-extinction uncertainty is analogous to demographic uncertainty for single
populations. This is a threat if the network containing the metapopulation only has a few
habitat patches and the local populations have a high risk of extinction (Barbault &
Sastrapradja 1995).
Regional uncertainty is equivalent to environmental uncertainty for single populations.
The risk of extinction by regional uncertainty decreases as the distance between
subpopulations increases (Barbault & Sastrapradja 1995). The picture shows a diagram
of a mountain (or bighorn) sheep (Ovis canadensis) metapopulation.
Scientific Conservation Action in Response to Population Decline
In this course, we have considered various forms of systematic (chapters 2—5) and
chance threats (this chapter) to species persistence. So, how does conservation deal with
these threats?
Conservation biologists have to deal with those species that have already been reduced to
remnants and attempt to prevent more species from reaching this remnant status. On the
premise that prevention is better (and possibly cheaper) than cure, a scientific approach to
identifying and mitigating (if possible reversing) a population decline will be presented
first.
The first step is understanding that a sustained population decline signals a conservation
problem (Caughley & Gunn 1996). The implication of this is that longer term population
declines need to be identified and confirmed. This is particularly important because
acting after the population is severely reduced makes identifying the cause of the
reduction difficult. The species may be lost before action can be taken (Caughley &
Gunn 1996) as happened with the large blue butterfly (Maculinea arion) in Britain
(Elmes & Thomas 1992, Caughley & Gunn 1996). The identification of population
declines relies, where possible, on monitoring either population size or the range of the
species. In the absence of enough monitoring data to meet the requirements of statistics
to provide an estimate of population size, the knowledge of local people is the best
available information. This knowledge should never be ignored (Caughley & Gunn
1996).
The next step is to develop a basic understanding of the species ecology (or ‘life history’
- i.e. such things as habitat and food preferences – not, at this stage, detailed demographic
studies). This knowledge is necessary for diagnosing the cause of the population decline
and for efforts to promote the recovery of the species (Caughley & Gunn 1996). The
large blue butterfly (Maculinea arion – pictured) became extinct in Britain because its
specialist relationship with its ant host (Myrmica sabuleti) was not understood (Elmes &
Thomas 1992).
Taking the ecological knowledge into consideration, all possible causes of the decline
should be listed. Thereafter, the level of each possible cause should be obtained in
relation to the present distribution of the species and its past distribution. Should the
results indicate that a particular cause is likely, a hypothesis is created.
This hypothesis must be tested by experimentation to be sure that the possible cause is
actually causing the decline. This is necessary for effective conservation action to ‘treat’
the problem and potentially saves time and money that would be spent on useless action.
It is possible maybe even probable that a combination of causes will be identified
(Caughley & Gunn 1996).
Once the cause(s) of a decline is(are) identified, possible actions to remove and neutralise
it(them) should be tested for effectiveness by experimentation (not only by modeling).
Plans for action need to include projections of population trends and identification of
potential measures to cope should the population recover to point where it exceeds its
carrying capacity. All plans for action must involve monitoring (Caughley & Gunn
1996).
Monitoring
The status of a species can only be determined by monitoring it (Primack 1998).
Monitoring is also necessary to judge the effectiveness of conservation actions (Caughley
& Gunn 1996).
Monitoring may take three forms. Inventories are counts of the number of individuals in
the population or the number of species in a community (Primack 1998). Surveys are
estimates of population size based on sampling. They are used where populations are
large or cover an extensive range. Surveys are methodical and repeatable though very
time consuming. They are especially useful where populations have stages in the life
cycle that are difficult to identify or locate (Primack 1998). Game counts, a form of
survey, may be done from the air as shown in the pictures. Demographic studies follow
known/‘marked’ individuals through their life cycle. Individuals of all ages and sizes
must be included in such studies. These studies provide the most comprehensive
information and may suggest management actions to ensure persistence. The down side
is that such studies are time consuming and expensive since repeated visits are required
(Primack 1998).
The effectiveness of monitoring depends on the scale at which it is carried out (Pullin
2002). The information from monitoring may be used for population viability analysis.
Population Viability Analysis
Population viability analysis (PVA) is a risk assessment for populations or species based
on empirical data that estimates the probability (risk) of extinction for a population of the
specific species for a selected time interval (e.g. 5% extinction probability (= 95%
probability of survival) for 100 years) (Frankel et al. 1995, Caughley & Gunn 1996, Cox
1997, Menges 2000, Wikipedia Contributors 2006c).
Three approaches to PVA exist: pattern analysis of long term studies, subjective
assessment using decision analysis based on expert knowledge and mathematical and/or
statistical modeling (Begon et al. 1996, Cox 1997). The most commonly discussed
approach is modeling (Caughley & Gunn 1996, Primack 1998, Menges 2000, Chapman
et al. 2001, Coulson et al. 2001, Pullin 2002).
All the approaches require information. The choice of approach depends on the quality
and quantity of data available. Long term data sets are not usually available for
endangered species (Coulson et al. 2001, Wikipedia Contributors 2006c) which reduces
the reliability/accuracy of models (Menges 2000, Coulson et al. 2001) and rules out
pattern analysis. The picture shows bighorn sheep (Ovis canadensis) which have been
studied for about 70 years – an example of a long term data set (Primack 1998).
Population Viability Analysis – Information Needed
All the approaches to PVA require information (Begon et al. 1996). The mathematical
and statistical modeling used in PVA requires lots of detailed ecological information on
the growth and vital rates of the selected species to have any degree of accuracy (Primack
1998, Coulson et al. 2001, Pullin 2002, Wikipedia Contributors 2006c). If one is to gain
an accurate extinction probability for t years from a model, one needs an estimated 5t –
10t years of data (Wikipedia Contributors 2006c). For most threatened species such data
are unavailable so decisions have to be taken without adequate information (Primack
1998, Coulson et al. 2001, Pullin 2002, Wikipedia Contributors 2006c).
For each species, information is required on the: morphology (for identification among
other things), environment (e.g. habitat, area, variability and human impact), distribution
(e.g. within its habitat, geographic, etc.), biotic interactions (e.g. competition and
predation), behaviour (e.g. reproductive), population demography (e.g. age distribution
and size over time), genetics (e.g. the degree of genetic control of morphological and
physiological traits) and physiology (e.g. physical requirements) (Primack 1998).
This information may be compiled from: published literature (such as the journal
‘Conservation Biology’), unpublished literature, fieldwork, the knowledge of experts and
the knowledge of locals (which should be used with caution but not ignored) (Begon et
al. 1996, Caughley & Gunn 1996, Primack 1998). The internet is increasingly important
for accessing literature (Primack 1998).
Uses of Population Viability Analysis
PVA may be used to: estimate the extinction probability for a population; determine the
minimum viable population; determine minimum reserve size– the area needed to
support an MVP; predict future population size; determine the IUCN status of the
species; show the importance of recovery efforts; identify key stages of the life cycle on
which to focus recovery efforts; compare proposed management options and develop
action plans for recovery efforts (this use of comparing management actions and planning
recovery efforts is potentially dangerous because PVAs consider the population size
without identifying the cause of a decline in size); evaluate existing recovery efforts (in
conjunction with monitoring) and explore and evaluate the potential impacts of habitat
loss, habitat fragmentation and habitat disturbance/degradation or the consequences of
various assumptions for small populations (Begon et al. 1996, Caughley & Gunn 1996,
Cox 1997, Primack 1998, Chapman et al. 2001, Coulson et al. 2001, Pullin 2002,
Wikipedia Contributors 2006c).
One of the earliest (perhaps the first) PVAs done on plants was done by Menges in 1990
on Furbish Lousewort (Pedicularis furbishiae) – pictured. It showed that metapopulation
dynamics were important in the survival of Furbish Lousewort (Frankel et al. 1995).
Minimum Viable Population
The minimum viable population (MVP) may be defined as the lowest number of
individuals needed to ensure that a population has a selected probability of survival for a
set time period without significant loss of evolutionary adaptability (Frankel et al. 1995,
Cox 1997), sometimes stated as the threshold below which a population will decline to
extinction (Caughley & Gunn 1996, Pullin 2002).
Shaffer (not the first to define the concept) selected a 99% probability of survival for
1000 years (Frankel et al. 1995, Primack 1998, Pullin 2002). While desirable, these
criteria are unrealistic if one considers the accuracy of calculations for such long term
predictions (Frankel et al. 1995, Pullin 2002). Few populations of plants would meet
these criteria (Frankel et al. 1995). A selection of parameters, that may be achievable, is
a 95% survival probability for 100 years (Groombridge 1992, Pullin 2002).
An MVP for a species is an estimate and therefore not a unique number (Frankel et al.
1995, Wikipedia Contributors 2006d). No MVP is applicable to all species
(Groombridge 1992, Barbault & Sastrapradja 1995).
Three further points should be noted concerning an MVP: it is applicable to a particular
habitat in an ecological context; if it includes genetic parameters, it is usually an estimate
of the effective population size not the actual population size needed and the level
(subpopulation/population, metapopulation or species) at which the MVP is applied must
be specified (Frankel et al. 1995).
It may be beneficial to consider an MVP in terms of the area needed to support it (the
minimum dynamic area (MDA)) (Frankel et al. 1995, Primack 1998). The picture shows
grizzly bears (Ursus arctos horribilis). Various people have estimated the MVP and
MDA for grizzly bears (Primack 1998).
Additional Notes
The 50/500 rule (of thumb - guideline): Franklin suggested that an effective population
size of 50 individuals is necessary to avoid inbreeding depression and an effective
population size of 500 individuals is necessary to prevent loss of genetic variation. The
latter figure is based on the mutation rate in Drosophila and represents the size needed
for the loss of allelic diversity to be balanced by mutation (Begon et al. 1996, Primack
1998, Pullin 2002). Implementation of this rule of thumb is problematic because the
effective population size may be much smaller than the actual population size (Primack
1998). Such guidelines should be used with caution – there is no single MVP for all
species (Begon et al. 1996, Caughley & Gunn 1996).
Effective Population Size
The effective population size (Ne) equals that of an ideal population that is genetically
influenced by random genetic drift in the same measure as the actual population (N). In
an ideal population, mating is random and the variation in individual progeny (offspring)
numbers is random. The following specifications are part of the definition of an ideal
population: for animals, a 1:1 sex ratio exists and for plants, all individuals reproduce
sexually and are diploid and bisexual, simultaneously producing female and male
gametes with a self-fertilisation rate of Ne-1 (Frankel et al. 1995, Cox 1997). More
simply phrased, it is the average number of individuals breeding successfully with the
assumption that gene contribution to the next generation is equal (Fiedler & Jain 1992,
Pullin 2002).
Effective population size is frequently less than actual population size because all
nonreproductive individuals (because of immaturity, age or lack of reproductive success)
are excluded (Primack 1998, Pullin 2002, Wikipedia Contributors 2006e).
The picture shows an Emperor Penguin (Aptenodytes forsteri) breeding colony with a
chick and its parents in the foreground. The effective population size for the Emperor
Penguin equals the number of adults in the colony when both parents are present. Nonbreeding or unsuccessful adults are not present in the colony but form part of the actual
population size as do the chicks in the colony.
Factors Affecting Effective Population Size
The effective population size (Ne) is affected by: unequal sex ratios including those
produced by social systems such as polygamy or, in plants, self incompatibility;
variation in reproductive output (the number of progeny produced) of both male and
female individuals because this leads to disproportionate representation of the genes of a
few individuals (of both sexes) in the next generation; population fluctuations because
Ne is strongly influenced by the smallest population size (termed a population bottleneck)
experienced by the population; whether or not generations overlap because overlapping
generations are less affected by genetic drift; age structure because fecundity and
mortality may be age-specific; dispersal because migration reduces genetic drift; the
distribution of individuals (also termed neighbourhood size) because this affects which
individuals are spatially capable of breeding with each other and inbreeding (which is
especially important in plants because some are self-pollinating), the occurrence of which
reduces Ne (Frankel et al. 1995, Begon et al. 1996, Caughley & Gunn 1996, Dobson
1996, Cox 1997, Primack 1998, Pullin 2002).
The top picture shows the African Wild Dog (Lycaon pictus). Only the alpha female of a
pack breeds (Wikipedia Contributors 2006f) so the sex ratio is skew as a result of the
social system. The bottom picture shows pine tree pollen adapted for wind dispersal.
Population Viability Analysis Using Modeling
The use of models for PVAs requires caution and common sense. A slight change in the
parameters combined with a change in the assumptions the model is based on may give
very different results (Primack 1998). The validity of a PVA depends on the model’s
quality and structure (Wikipedia Contributors 2006c). Models may not include enough
ecology to be reliable (Caughley & Gunn 1996, Watson et al. 2005) as was found to be
the case for the model used to study the Cape Mountain Zebra (Equus zebra zebra pictured) in the Gamka Mountain Nature Reserve, South Africa (Watson et al. 2005) and
was demonstrated for two models attempting to predict the extinction probability for the
Soay sheep (Ovis aries) (Chapman et al. 2001).
Two conditions need to be met for a PVA to be reasonably accurate: the data must be of
adequate quality and the future vital rates for the population need to be similar to the
present rates used in the model. The latter condition can usually not be guaranteed
(Coulson et al. 2001).
Computer programs do exactly what they have been told to do within the constraints of
the model used. The user must have a basic understanding of ecology and the ecology of
the specific species to know when different models are adequate (Caughley & Gunn
1996).
The process of selecting a model needs to consider whether the model assumptions are
applicable in the population to be studied and whether the data are adequate to provide
reliable inputs into the model. The form of density dependence needs to be taken into
account in choosing a model. The model needs to reflect the mechanisms of population
regulation or the results will be unrealistic (Chapman et al. 2001). PVA software
packages include INMAT and VORTEX. VORTEX is more flexible than INMAT
(Chapman et al. 2001). Scientific testing of models is necessary to determine reliability
(Caughley & Gunn 1996).
The use of PVAs does not replace monitoring (Primack 1998, Pullin 2002). PVAs are
used on threatened species or species suspected of being under threat, but what causes
suspicion that a species may be vulnerable to extinction?
Vulnerability to Extinction
While the conservation priority of a species is based on the level of threat of extinction
that it faces (Pullin 2002, see also chapter 6 of this course), there are some life history
traits that can be used as a guide to the sensitivity of species to habitat fragmentation and
human disturbance (Groombridge 1992) and therefore also as a guide to which species
should be monitored (Caughley & Gunn 1996). A single species may have several of
these traits because these traits are not independent (Groombridge 1992, Primack 1998).
Several of the categories in the following slides may include common species. The
passenger pigeon was abundant and widespread prior to its extinction (Leakey & Lewin
1995) – see chapter 3 of this course. Abundant species are not adapted to cope with small
population sizes and are thus vulnerable if reduced to small populations (pers. comm. Dr
R.S. Knight 2006).
The following slides give a brief overview of the identified categories of traits that make
species vulnerable to extinction. The picture shows a drawing of Gladiolus carinatus
(the blou-afrikaner or sandpypie). Most years, many plants are pulled up by people
collecting the flowers for some purpose, possibly to sell or for their fragrance and beauty
(pers. obs.).
Vulnerability to Extinction 2
The following categories of species are vulnerable to extinction. Species that only occur
in threatened habitat types (Barbault & Sastrapradja 1995) (e.g. tropical forest species)
because no species is capable of surviving the sudden and total removal of its habitat. If
the habitat is fragmented, the carrying capacity (the largest sustainable population size) of
the individual habitat fragments is determined by the area of each habitat fragment
(Pullin 2002). Species that are economically valuable to humans are threatened by
overexploitation resulting from both legal and illegal harvesting (Cox 1997, Primack
1998) – see chapter 3 of this course. Species that do not have any/much experience of
disturbance are unable to tolerate major disturbances and may not be readily able to adapt
to disturbance (Barbault & Sastrapradja 1995, Primack 1998). Species that have evolved
in isolation within a limited community without human contact are at risk because of
their endemic status and because isolation may have made them unable to cope with
competition and predation from introduced species (Barbault & Sastrapradja 1995,
Dobson 1996, Cox 1997, Primack 1998) – see the Invasion Biology Course and chapter 4
of this course. Specialist species are vulnerable because of their dependence on a limited
range of resources and conditions that may not endure after pollution (Groombridge
1992, Cox 1997, Primack 1998). Species that depend on unreliable resources are
vulnerable (Barbault & Sastrapradja 1995) to disturbances that affect their required
resources. Species requiring large home ranges are vulnerable to habitat changes
(Primack 1998). Species that have declining populations are vulnerable if the cause of
the decline is not recognised and corrected (Primack 1998). Declining populations that
are not identified (see slide 9 on scientific conservation action in response to population
decline) will eventually drop below the MVP and get caught in an extinction vortex
(Primack 1998).
Additional Notes:
An extinction vortex may be defined as a set of positive feedback loops of deterministic
and stochastic events that further decrease population size most likely causing extinction
(Fiedler & Jain 1992, Primack 1998).
Vulnerability to Extinction 3 - Rarity
Three parameters are used to identify species abundance. They are geographical range,
habitat specificity and population size. Combined they give 8 categories of which 7 are
considered rare (Begon et al. 1996, Primack 1998, Pullin 2002). All forms of rarity may
come under threat and require conservation action (Begon et al. 1996).
Table 7.1: All the possible combinations of the three factors (geographic range, habitat
specificity and population size) influencing species abundance modified slightly from
Pullin (2002).
Geographic
Range
Large
Small
Habitat
specificity
Broad
Narrow
Broad
Narrow
Large population
size, dominant
somewhere
Locally
abundant in
several
habitats over
large range1
Locally
abundant in a
specific habitat
over a large
range
Locally
abundant in
several
habitats but
geographically
restricted
Locally
abundant in a
specific habitat
but
geographically
restricted
Small population
size, not
dominant
Always sparse
in several
habitats over a
large range
Always sparse
in a specific
habitat over a
large range
Always sparse
in several
habitats and
geographically
restricted
Always sparse
in a specific
habitat and
geographically
restricted
1
The only category that is not considered rare.
Vulnerability to Extinction 4The following categories of species are vulnerable to
extinction. Short-lived species (Groombridge 1992) have less chance of surviving long
enough to adapt to disturbance than do longer lived species. Species with a low adult
survival rate are potentially more vulnerable to extinction (Groombridge 1992). Species
with low genetic variability (e.g. the Cheetah (Acinonyx jubatus)) may be unable to adapt
to changing conditions (Primack 1998). Species with a low intrinsic growth rate take a
long time to recover from chance population reductions (Groombridge 1992). Species
with very variable population size risk declining below the MVP (Groombridge 1992).
Species that lack long distance dispersal mechanisms are unable to migrate in response to
rapidly changing conditions to which there might not be time to adapt resulting inevitably
in extinction (Groombridge 1992, Barbault & Sastrapradja 1995, Dobson 1996, Primack
1998). Species that form aggregations, either permanent or temporary (e.g. colonial
nesting such as the Cape Gannets (Morus capensis)) are vulnerable to exploitation and
potentially to the break down of the social structure if the population declines below the
threshold required for social interactions (Barbault & Sastrapradja 1995, Cox 1997,
Primack 1998). Migratory species (e.g. Greater Striped Swallows (Hirundo cucullata) –
pictured) depend on more than one habitat type over a large geographical area increasing
the risks of habitat changes creating barriers to migration and the chances of
overexploitation (Barbault & Sastrapradja 1995, Dobson 1996, Cox 1997, Primack 1998).
Large species (e.g. Blue Whales (Balaenoptera musculus), Elephants (Loxodonta
africana) and Coast Redwoods (Sequoia sempervirens)) are vulnerable to exploitation or
eradication because of competition for resources (e.g. top carnivores) (Barbault &
Sastrapradja 1995, Dobson 1996, Primack 1998). Species feeding at a high trophic level
are not abundant and are vulnerable to any disruption of the food chain as well as to the
increasing concentration of certain toxins as one moves up a food chain (Groombridge
1992, Barbault & Sastrapradja 1995, Dobson 1996, Cox 1997).
Points to Ponder
That which harms biodiversity will eventually harm humanity (Primack 1998).
No population survives forever (Primack 1998). Population size is critical to survival
(Barbault & Sastrapradja 1995).
Monitoring is critical to identifying threatened populations/species (Caughley & Gunn
1996).
Population viability analysis is a conservation tool that needs to be used with caution
(Caughley & Gunn 1996, Primack 1998).
Identifying and mitigating/removing (if possible) the causes of population decline are as
important as striving to protect the reduced population from stochastic events as the
reduced population will not be able to increase substantially without the mitigation of the
original causes of decline (Caughley & Gunn 1996). The above statement suggests that
conservation biology needs to focus some efforts on reducing the ultimate cause of
species population decline viz. human population expansion.
Sharing information (including - but not limited to - via education) is central to achieving
changes in human attitudes and behaviour.
Last slide
I hope that you found chapter 7 informative and that you will enjoy chapter 8.