Download Colonization in metapopulations: a review of

RioloRical Journal qf the Linnean Society (1991), 42: 105-121. With 1 figure
Colonization in metapopulations: a review of
theory and observations
TORBJORN EBENHARD
Section of Animal Ecology, Department of <oolosy, Universily of Uppsala, Box 561,
S-751 22 Uppsala, Sweden
In metapopulation dynamics turnover of populations in isolated patches may be frequent. Regional
survival of a species in such a system with frequent extinctions hinges on its colonization ability.
Colonization is more than just dispersal; when a propagule reaches a new patch i t Faces higher
extinction probabilities than does an established population. Extinction models as wrll as empirical
data suggest that a large propagule with a potential for rapid increase in a varying environment, 01
with a low mortality rate in an environment perceived as constant, has a higher probability of
successful colonization. Large variation in population size when it is still small increases the risk of
failure. Factors introducing such variation are dcmographic stochasticity and environmental
variation. It is hard to single out demographic traits that ensure good colonizing ability, since
colonization can be achieved in many direrent ways, but generalists and species with selffertilization seem to be superior.
KEY WORDS:-Metapopulation - colonization - extinction models - propagule
stochasticity - habitat fragmentation - patchy habitats.
CONTENTS
Introduction . . . . . . . . . . .
Colonization theory . . . . . . . . .
Assumptions . . . . . . . . . .
Predictions . . . . . . . . . .
The empirical study of colonization
. . . . .
Experimental introductions
. . . . . .
Natural colonization in metapopulations . . .
Natural colonization of defaunated islands . . .
Distribution patterns . . . . . . . .
Discussion.
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Acknowledgements
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Referenres
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III
1I 1
I 14
I 14
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I I7
I18
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INTKODUC'I'ION
Early metapopulation models, such as Levins's (1969) model (reviewed by
Hanski, 1991) make the simplifying assumption that habitat patches are in one
of two alternative states, occupied or not occupied. All populations in occupied
patches are assumed to be at their carrying capacity, K . Such simple models
further assume that the regional dynamics may be modelled by just two
parameters, determining the colonization rate ( m ) and extinction rate (e) of local
populations. An important qualitative prediction from these models is that the
colonization rate must exceed a threshold value for the species to survive
regionally (e.g. Hanski, 1982, 1983, 1985).
0024-4066/9 1 /010105
+ 17 SOS.OO/O
I05
8 1991 'l'he Linnean
Society 0 1 London
I06
T. EBENHARD
Colonization can be dissected into several processes, starting with the
emigration of individuals from an occupied patch and the subsequent dispersal
through a more or less inhospitable habitat matrix (reviewed by Hansson, 1991).
Immigrating individuals then face the problems of surviving and reproducing in
a new habitat patch, in what is here called the colonization process proper.
Colonization is defined as starting with the arrival of a propagule (the
immigrating individuals) and ending when the extinction probability of the
population is no longer dependent on the initial state (i.e. the propagule
properties). This definition highlights the stochastic nature of the colonization
process (Simberloff, 1988) and the often considerably higher extinction
probability of a colonizing population in comparison with a fully established one
(Williamson & Brown, 1986; Ehrlich & Murphy, 1987).
If the parameter m in a metapopulation model is defined as a pure dispersal
parameter (e.g. Stenseth, 1977; Shaffer, 1985), then extinctions during the
colonization proper must be included in the extinction parameter e, which
implies that the extinction probability for the propagule of size x is taken to be
identical to that of a population at some ‘equilibrium’ size K , unless e is treated
as a function of population size (Stenseth, 1977, 1981; Hanski, 1991). A better
solution would be to include the complete colonization process in m, although
this might affect the choice of a time step. This would be more useful in
empirical studies, in which often the result of colonization rather than the
process itself is observed (e.g. Pokki, 1981; Bengtsson, 1988, 1991). This
definition of colonization does not preclude the possibility that propagules in the
process of establishing themselves may emit propagules to other patches.
In a wider context, the expression ‘colonization’ has several meanings, not all
of them pertinent to metapopulation dynamics. In a classical metapopulation
model all habitat patches are by definition inhabitable, and the surrounding
environment is inhospitable. Furthermore, turnover is a dynamic process within
the boundaries of the patch system. Thus, colonization in the meaning of passive
sampling of individuals from a population that is widely distributed in the
surrounding matrix (e.g. Southwood & Kennedy, 1983; Webb, 1989) or from
outside the boundaries of the metapopulation (Haila, 1983), may be
inappropriate notions of colonization in this context.
Colonizations are, by definition, taking place only in previously empty habitat
patches. Immigrating individuals may, however, reach occupied patches as well.
Immigration to existing populations is of importance to metapopulation
dynamics, especially to the extinction rates of small populations, by offering gene
flow that may eliminate inbreeding (Gilpin, 1987) and by augmenting ailing
populations (rescue effect, Brown & Kodric-Brown, 1977; Hanski, 1991).
COLONIZATION THEORY
Propagules that fail to colonize become extinct, and most of the theory
regarding colonization stems from extinction models. A diverse collection of
population extinction models has been constructed, ranging from simple
equations to elaborate simulation models with numerous parameters. The
assumptions and predictions of the extinction models are equally diverse, making
comparisons between models and with empirical data difficult.
The models described below were not constructed within a metapopulation
context, but they may still offer insights. The following review of models only
COLONIZATION IN METAPOPULATIONS
107
TABLE
1. A summary of assumptions and predictions of colonization models and other relevant
extinction models. D, homogeneous demographic stochasticity; H, heterogeneous demographic
stochasticity; E, environmental stochasticity; P,(K,x), probability to reach carrying capacity X
from propagule size x; I,,time to extinction starting at propagule arrival; 'I;;,time to extinction
starting at K; n,, critical population size; 1, natality rate; p, mortality rate; r, rate of increase
Model
MacArthur & Wilson (1967)
Assumed
stochasticity
Predictions
Parameter
Dependent on
D
9dbx)
41(>x
eh
4r9 x
Richter-Dyn & Goel (1972)
D
Same as for
MacArthur/Wilson
Existence of n, < X
Leigh (1981)
Variance in r, InK
Variance in r, x , lnK
Ehenhard (unpublished)
H
P,Y(KJ)
4P3 x
Strebel (1985)
E
T
A
Frequency of variations in K
D+E
T
A
InK
Goodman (1987a-c )
considers aspects applicable to metapopulation dynamics, and is not intended as
an evaluation of the models as such.
Population survival can be expressed in several ways. A common variable is
the mean expected time to extinction T (e.g. MacArthur & Wilson, 1967). I t is
often useful to define a starting point for the calculation of T, e.g. at the time of
or after the point at which a population has first
immigration of a propagule
The probability of a propagule of size x to
reached an equilibrium size ( TK).
reach an equilibrium population size K, P,(X,x), is another useful parameter
(Richter-Dyn & Goel, 1972). Another measure of population survival is the
minimum viable population size (MVP), which is the smallest population with a
certain preset probability to survive a certain period of time (Samson, 1983;
Shaffer, 1983). Only models using
or P,(X,x) can be used as models of
population colonization. Examples of such models are those by MacArthur &
Wilson (1967), Richter-Dyn & Goel (1972), Leigh (1981) and Ebenhard
(unpublished).
Colonization models may be similar to other extinction models, but they
always assume a priori that the starting population size is different from the
equilibrium size. Furthermore, extinction probabilities during the colonization
may be dependent on parameters which are less important when the population
has reached its equilibrium size, and vice versa. Two additional pure extinction
models, those by Strebel (1985) and Goodman (1987a-c), offer additional
predictions by inference. Table 1 summarizes the six models.
(x)
Assumplions
An important fact of small populations is uncertainty (Tuljapurkar, 1989),
hence all six extinction models employ stochasticity in one form or another.
I08
T. EBENHARD
Shaffer (1985) recognizes four different sources of stochastic variation in a
natural system, demographic, environmental, and genetic stochasticity, as well
as catastrophic events. Only demographic (all models except the Strebel model)
and environmental stochasticity (the Leigh, Strebel and Goodman models) have
been employed in the models in Table 1.
The stochastic variation in population size and demographic rates due to the
independent history of individuals is termed demographic stochasticity (see
Hanski & Gilpin, 1991). The amount of such variation in population size is a
function of population size. Assuming the simplest kind of demography, in which
all individuals are identical and all events occur randomly distributed over
individuals and time, the coefficient of variation in population size is I/JX,
where X is the equilibrium population size (May, 1973; Leigh, 1975; SoulC,
1983). As opposed to such a ‘homogeneous’ demography, a ‘heterogeneous’
demography results whenever individuals are different (sex, age), or events are
occurring with a non-Poisson distribution (e.g. time lags due to sexual
maturation time or gravidity time) (Ebenhard, unpublished). In such cases
variation in population size can be much greater (Goodman, 1987a). Among
these six models, only the Ebenhard model has heterogeneous demography, but
it has been employed in minimum viable population models as well (e.g. Shaffer,
1983).
Environmental stochasticity is intended to describe non-deterministic
variation in the environment, such as chance variation in resources and other
factors, such as weather, prey abundance and diseases. Under environmental
stochasticity, all individuals in a population are affected simultaneously (but not
necessarily equally), which makes variation in population size independent of X
(Gilpin & Soult., 1986). Leigh’s model introduces environmental stochasticity as
a randomly varying intrinsic rate of increase, r, as does Goodman’s model, while
X varies in Strebel’s model. The choice of the type of stochasticity constitutes an
important assumption concerning fundamental properties of a natural
metapopulation system.
Further assumptions, common to all six models, include the homogeneous
mixing (Mollison, 1986) of individuals; that is, potentially all individuals in the
propagule as well as in the established population may interact with each other.
In a metapopulation, this assumption is probably unnatural, since simultaneous
arrival of individuals in a propagule is unlikely. Propagule size may hence be
thought of as a correlate of immigration rate, with a correction for the expected
lifetime of individuals. Another assumption made in all models is the absence of
trends in deterministic factors.
With the possible exception of the homogeneous mixing assumption, all
assumptions made in the six extinction models may be appropriate in a
metapopulation context, but not necessarily in all situations.
Predictions
The MacArthur/Wilson model is a Markovian birth-and-death process model,
which relates, 7,, T,. and l‘,(K,x) to X, x , 1 and p. The colonization probability,
in this case the probability to reach the carrying capacity from the propagule
size, is given approximately by
PS(X,X) x 1 - ( P / V
(1)
COLONIZATION IN METAPOPULATIONS
109
given that x << K. When x = 1 this reduces to
Ps(K,l) x ( A - p ) / A = r/A.
Expression 2 has often but erroneously been interpreted to mean that a good
colonizer always has a high r. In this model, a high ratio of natality to mortality
and a large propagule size are the most important determinants of colonization
success. The time to extinction of a population varying around K, on the other
hand, was found to be a function of 8.This means that there exists a threshold
population size, above which extinction is highly improbable. 7, is a
conglomerate of times to extinction before and after K has been reached, and is
hence dependent on both the demographic rates and X. In the
MacArthur/Wilson model A/p can also be expressed as R,, the net reproductive
rate (Armstrong, 1978), but this approximation does not hold for the following
models.
The Richter-Dyn/Goel model is quite similar to the MacArthur/Wilson
model, but has a logistic density dependence. The predictions from this model
are also similar, including the existence of a critical population size, above which
extinction is highly improbable. This critical population size is the size at which
the population is defined to be established, i.e. when the future extinction
probability is independent of propagule size.
The Ebenhard model is a more complicated simulation model with
heterogeneous demography. Regarding Ps(X,x) this model gave qualitatively the
same predictions as the two preceding models (colonization success depends on
Alp and propagule size), but for similar values of Alp and x, the Ebenhard model
predicted much lower colonization probabilities. As heterogeneous demography
changes the distribution in time and among individuals of positive events
(births) in relation to negative events (deaths), with positive events more
clumped to certain individuals or time periods, the best strategy to maximize A/p
is to decrease p, the rate of negative events. Further predictions were that
demographic traits connected with a more homogeneous demography, such as
short rather than long time lags (e.g. gravidity time), small and frequent litters
instead of larger and more infrequent ones, as well as asexual reproduction,
increase the probability of successful colonization (Fig. 1). In both the
MacArthur/Wilson and the Richter-Dyn/Goel models T, increases
exponentially with X . The heterogeneous demography of the Ebenhard model
does not change the shape of that dependence, but the exponential increase will
be slower.
The Leigh model is also a Markovian birth-and-death process model, relating
and T , to r, K, and the amount of environmental variation in r. All three
parameters were found to influence time to extinction, but variance in r was the
most important one, through its effect on the amplitude of population
fluctuations.
The most important predictions of the Goodman model is that under
environmental stochasticity, the time to extinction from X is a function of InK,
and that there is no critical population size which would ensure long persistence.
The Strebel model assumes logistic population growth coupled with
randomly varying carrying capacity K. In this model 7, is related to X and its
frequency of variation, r and the generation time. T[ was found to be mainly a
function of the frequency of environmental fluctuations in X. This offers two
<
110
T. EBENHARD
I
2
5
10
/P
Figure 1. The probability of reaching carrying capacity ( K ) from a propagule of size x as a function
of the natality to mortality ratio ( U p ) in Ebenhard’s model. A comparison of the effects of
homogeneous (filled dots) and heterogeneous demography (squares = gravidity time (G) 5 units
instead of 1, circles = litter size (L) 2 instead of 1, triangle =sexual reproduction instead of
asexual). The result with only homogeneous demographic stochasticity corresponds to that of both
MacArthur & Wilson (1967) and of Richter-Dyn & Goel (1972).
different strategies of population survival, in relation to the generation time.
Periods of worse conditions should either be averaged out through long
generations (low p), or tracked with a high r. The latter two models do not
formulate q,.but assuming environmental variations to be pronounced during
the colonization, their predictions should apply to that process as well.
To summarize, if the environment is predictable (only demographic
stochasticity) a good colonizer should have a high ratio of natality to mortality,
best achieved through low mortality. Otherwise, a high and invariable r is
advantageous, unless the bad times can be averaged out with a low rate of
mortality. The ratio Alp has no dimension, whereas r is expressed per unit time.
When time is important, as in a recovery of a population from low density before
the next unfavourable period starts, r is probably a better predictor of
colonization success than is the ratio A/p. A good colonizer should also be a good
disperser, ensuring the arrival of large propagules.
Traditionally, good colonizers have been believed to be r-selected (Lewontin,
1965; Pianka, 1970; Safriel & Ritte, 1980, 1983)) which is not necessarily true,
COLONIZATION IN METAPOPULATIONS
111
since r is not always the critical demographic parameter. A host of characters
correlated with natality and mortality rates, such as large litter size, short
generation time, small body size (high r), or large body size (high Alp, better
ability to withstand stress) have been put forward as important attributes of a
good colonizer. Often generalists have been considered to make better colonizers
(Grant, 1970; Graves & Gotelli, 1983; Ehrlich, 1986; Baur & Bengtsson, 1987)
than specialists. The age composition of the propagule may also be important
(Williamson & Charlesworth, 1976), as it will influence the reproductive value of
the propagule (MacArthur & Wilson, 1967). Finally, asexually reproducing
species may have a generally higher colonization success than sexually
reproducing ones (Jain, 1976; Brown & Marshall, 1981; Baur & Bengtsson,
1987).
THE EMPIRICAL STUDY OF COLONIZAllON
Colonization studies in natural systems have encountered at least three major
difficulties. Except under controlled laboratory conditions (e.g. Forney & Gilpin,
1989), it has been difficult to estimate the relative importance, or even the
existence of different types of stochasticity. Another difficulty concerns the
variables describing demography in the models, r, 1and p. These variables are
often extremely hard to estimate in natural populations, not to mention their
temporal and spatial variation. This means that it has been very difficult to test
Strebel's (1985) predictions about the effect of r in relation to the frequency and
duration of environmental disturbances. Thirdly, patterns due to the
colonization process may often be altered by other processes, e.g. extinctions or
adaptations long after the establishment of new populations. This problem
pertains especially to studies of species distributions in archipelagoes or other
fragmented areas with slow or no turnover.
The empirical studies described below are of four kinds, namely experimental
introductions, natural colonizations within metapopulations with turnover,
natural colonizations of defaunated islands and the study of distribution patterns
and characteristics of species with wide distributions on islands. All such studies
contribute to the understanding of the colonization process and offer possibilities
to test the theoretical models.
Experimental introductions
Sheppe (1965) made an early experiment with the white-footed mouse
(Peromyscus leucopus (Rafinesque)). He planted propagules ranging in size from
two to ten individuals on small islands in a lake, and related colonization success
to the initial density (not absolute numbers) of mice. No effect of density was
found, but Sheppe reported a higher colonization success on larger islands,
which may have been a propagule size effect, since he released more mice on
larger islands.
Crowell ( 1973) introduced red-backed voles (Clethrionomys gapperi (Vigors))
( N = 1 1 propagules) and deer mice (Peromyscus maniculatus (Wagner)) ( N = 12)
to small islands off Maine, in an experimental test of the MacArthur/Wilson
model. As expected, both demography and propagule size had effects on
colonization success. The vole had a ratio of natality to mortality (Alp) of 1.08,
I12
T. EBENHARD
while the respective ratio for the mouse was 1.43. The deer mice propagules were
found to be more successful as expected. The meadow vole (Microtus
Pennsylvanicus (Ord)), with A/p = 1.84, was the only native rodent found to be
widespread in the archipelago. This experiment could not distinguish between
the effects of the ratio Alp and the intrinsic rate of increase r, since the r values of
the three species covaried with the ratios (Clethrionomys: r = 0.23, Peromyscus:
r = 0.55, and Microtus: r = 2.48). Propagule sizes varied between two and 16
individuals, and in both species larger propagules had higher success of
colonization.
Mehlhop & Lynch (1978) introduced white-footed mice to two small islands
in Chesapeake Bay, using large propagules (28 and 30 mice). Both introductions
were successful, but population increase was much slower on one of the islands,
due to heavier mortality caused by a lack of refuges from predators on that
island. This result exemplifies spatial variation between habitat patches in the
values of p.
Working on small Caribbean islands, Schoener & Schoener (1983) released 25
propagules of small lizards (Anolis sagrei DumCril & Bibron), using five or 10
lizards on each island. Most colonizations were successful; populations with both
sexes present were found on 18 islands in the following year. No effect of
propagule size on colonization probability was found, but as the ratio A/p was
very high (2.52) this is expected from expression 1, with Ps(K,x) x 0.99 for five
lizards and 1.00 for 10 lizards. Schoener & Schoener also found an area effect,
with longer times to extinction on larger islands. No colonization model predicts
area to be important in colonization, but as some of the islands were sufficiently
small to make the propagule an instant carrying-capacity population ( x x x ) ,
the pattern found is consistent with the dependence of 7,on K . This experiment
thus involved both colonization and extinction in ‘established’ but very small
populations. There may have been a behavioural area effect during the early
stages of colonization, as the propagules probably left the smallest islands by
swimming.
In a test of the MacArthur/Wilson, Richter-DynlGoel and Ebenhard models,
Ebenhard (1987a, 1989) used bank voles (Clethrionomys glareolus (Schreber)) of
two different provenances, and with different demography. Laboratory studies
showed that voles from northern Sweden (N-population) had a much higher
reproductive rate than voles from southern Sweden (S-population), mainly due
to a larger litter size in N-voles. The northern voles were thus predicted to be
better colonizers, but when voles of the two provenances were released on 20
islands each in the Baltic Sea, the opposite result was obtained (Table 2). The
explanation was that the N-voles suffered much higher adult mortality rates
(0.031 per vole and day) than did the S-voles (0.015), resulting in a very low
ratio of natality to mortality (0.80 us. 1.12 in S-voles). This increased mortality
may have been caused by the higher activity of the N-voles (Ebenhard, 1987).
Four different propagule sizes were used, two, four, ten and 20 voles, and among
the S-voles larger propagules were more successful (Table 2).
Harrison (1989) made 38 introductions of the Bay checkerspot butterfly
(Euphydryas editha bayensis Boisduval) to empty habitat patches, and she found
very low colonization frequencies: only six patches (16%) had a population
1 year later, despite large propagules (100 larvae in each). The low success of
colonization was probably due to slow initial population growth, as recorded in
COLONIZATION IN METAPOPULATIONS
I13
TABLE
2. A comparison of predicted and observed extinctions of vole propagules during experimental introductions (Ebenhard, 1989). The sample size is five islands in each case. Predicted
extinctions are given both from the Ebenhard model with heterogeneous demography, and from
the MacArthur/Wilson model with homogeneous demography. The Ebenhard model predicts
number of extinctions at the end of the test run, specifically, whereas the MacArthur/Wilson model
predicts the eventual result, without specifying a time scope. In order to fit these assumptions,
observed extinctions are given as complete extinctions and complete plus imminent extinctions
(only one sex present). Predicted and observed extinctions were tested pairwise with a binomial
test. P expresses probability of receiving observed number of extinctions or any more extreme value
Predicted
Volc
provenance
Propagule
size
Predicted
extinction:
Ebenhard
Observed
extinction:
complete
3.9
2.8
I .3
0.3
4
2.4
1.o
0.1
Observed
extinction:
MacArthurl complete+
Wilson
imminent
extinction:
Test P
Test P
~~
Northern
2
4
10
20
Southern
2
4
10
20
0.0
5.0
5.0
5.0
5.0
5
4
2
I .oo
I .oo
I .oo
0.03
4
4
0.20
0.01
4.0
3.1
4
4
2
3
1
0
0
I .oo
I .oo
1.6
0.5
1
4
1
~
I .oo
0.00
0.00
0.00
I .oo
0.66
I .oo
1 .oo
the patches where the butterfly did succeed, and a high variability in
environmental conditions.
In a literature study of bird introductions, Ebenhard (unpublished) examined
the effects of propagule size and several demographic parameters on colonization
success. A clear propagule size effect was found among 116 introductions of 56
different bird species. The median size of a successful propagule was 37, while
failing propagules had a median of ten individuals (P< 0.0001). Age of sexual
maturation or type of mating system had no effect, but clutch size showed a
positive trend (Spearman’s rank correlation, r = 0.23, N = 56, P < 0.1) and a
significant positive correlation was found between body length and colonization
success (Spearman’s rank correlation, r = 0.35, N = 51, P < 0.05). There was,
however, a correlation between body size and propagule size, so that larger birds
were introduced in larger groups.
A large number of attempts to introduce dung beetles (Scarabaeidae) have
been carried out worldwide, with varying success. Australia has received
propagules of at least 41 species, but only ten species have become established
and another 12 possibly so (Doube et al., 1991; Hanski & Cambefort, 1991). The
four most successful species form a heterogeneous group of dung beetles
ecologically, but share a number of attributes; they are medium sized
multivoltine beetles with rapid development and high fecundity (50-1 30 eggs
per female). These traits will render them a large A and probably r as well.
Furthermore, they seem to be generalistic with respect to preferred soil types.
Among the colonization failures, many species are larger with a very low
fecundity (close to one egg per female). However, one species with such a low
reproductive rate is at least locally abundant following a long period of slow
population growth. This may be an example of the importance of the ratio Alp
rather than r, assuming a low mortality.
114
T. EBENHARD
To summarize, these experimental tests of colonization models show that both
demography (e.g. Crowell, 1973; Schoener & Schoener, 1983; Ebenhard, 1987a)
and propagule size (e.g. Sheppe, 1965; Crowell, 1973; Ebenhard, 1989) are
important determinants of colonization success. The ratio of natality to mortality
has been shown to be important, but as the intrinsic rate of increase r was
correlated with R/p in these experiments (e.g. Crowell, 1973; Ebenhard, 1989),
we cannot distinguish between the effects of the two demographic parameters.
At this stage it is not possible to conclude much about the predictive powers of
the different models. Afurther complicating factor is that R and p are not
species-specific constants, but can vary considerably depending on the conditions
of the island to be colonized (Mehlhop & Lynch, 1978) and with time (Harrison,
1989), demonstrating the effect of environmental stochasticity.
.Natural colonization in metapopulations
In studies of natural colonization in metapopulations, propagule sizes are
either unknown or are expressed as rates of immigration of individuals.
However, given that propagule size is important to colonization success and that
immigration rates are distance dependent (see Hansson, 1991), then the pattern
of occupied patches in a metapopulation system is predicted to depend on
isolation. Such a situation has been found in several systems, including
metapopulations of the Bay checkerspot butterfly (Harrison et al., 1988), orb
spiders (Toft & Schoener, 1983), amphibians (Laan & Verboom, 1990.;
Sjogren, unpublished), the spruce grouse (Canachites canadensis (L.)) (Fritz, 1979),
shrews (Sorex) (Hanski, 199l ) , the pika (Ochotona princeps (Richardson)) (Smith,
1980), and the field vole (Microlus agrestis (L.)) (Pokki, 1981). Such patterns
may, however, also arise without any effect of the propagule size.
The effect of demography on colonization success is also often difficult to
assess, since usually only one species is studied in each system. Bengtsson’s study
of rockpool Daphnia (1991) involved three species, but he found no differences in
their colonization abilities.
Schoener & Spiller (1987) found extinctions to be most frequent in small and
newly established spider populations. An explanation may be that these
extinctions occurred during the colonization process rather than in established
populations close to K . If so, this supports the existence of a critical population
size below which a colonizing population has a higher extinction risk.
Some of these studies (Fritz, 1979; Smith, 1980) show that the time scales of
within- and between-patch dynamics may be quite similar. This means that the
turnover rate of populations approaches that of individuals, and many
populations will last only for a few generations (e.g. Addicott, 1978). In Smith’s
(1980) study of the pika each habitat patch was occupied by a family rather than
a population. With such small populations, the propagule size must inevitably be
very close to the carrying capacity, and the colonization process will depend
much more on the behaviour of individuals rather than on population
demography (MacArthur & Wilson, 1967).
Afatural colonization of defaunated islands
Data on the recolonization of defaunated islands are potentially relevant to
the testing of colonization models, but there are problems in interpreting the
COLONIZATION IN METAPOPULATIONS
115
data. The best way to test the models would be to analyse the colonization order
of different species in relation to their demographic attributes and dispersal
abilities. On islands which have been defaunated by natural catastrophes, such
as Krakatau (e.g. New et al., 1988) or Motmot Island (Ball & Glucksman, 1975),
the order of colonization is greatly influenced by the succession of vegetation on
the island. In experimental studies where only the animals have been removed,
leaving the vegetation intact, such as in the studies by Rey (Rey & Strong, 1983;
Rey, 1984) and Simberloff (e.g. Simberloff, 1981) , differences in colonization
ability between species have been observed, but no independent measures of the
dispersal ability or demography of the species concerned were provided.
Distribution palterns
Analyses of distribution patterns among islands, and comparisons between
species that had colonized and those which had not, may also give valuable
empirical information. A major problem with such analyses is that it may be
hard to distinguish between the effects of characters which facilitate colonization
and those which ensure long-time persistence on islands. The presence of a
species on an island may depend on processes other than just colonization.
Generalists have been predicted to be better colonizers than specialists,
because they are more easily able to find sufficient resources on an island to
achieve a high ratio of natality to mortality. Empirical evidence supporting this
prediction has been found for terrestrial snails (Baur & Bengtsson, 1987) and
carabid beetles (Niemela, Haila & Halme, 1988; As, unpublished) which have
colonized islands in the Baltic Sea, marine species colonizing the Mediterranean
Sea through the Suez Canal (Safriel & Ritte, 1983), lizards found on islands of
the Gulf of California (Case, 1975) and passerine birds introduced to Hawaii
(Moulton & Pimm, 1986). Baur & Bengtsson found a tendency for species with
self-fertilization to be better colonizers, as did Price & Jain (1981) for colonizers
in the British flora. Rydin & Borgegird (1988, and unpublished) analysed the
order of colonization of plant species on islands created in Lake Hjalmaren,
Sweden, following the lowering of the water level. They found pioneering species
to be self-fertilizing annuals which often lacked vegetative reproduction.
Several authors have tried to relate colonization success to the intrinsic rate of
increase, r, or some correlate of r, using Pianka’s (1970) concept of r- and
K-selection, with mixed results. Baur & Bengtsson (1987) found no correlation
between colonization order of snail species and any life-history trait related to
r-selection (e.g. age and size at maturity, life span, clutch size, net reproductive
rate). This does not necessarily mean that r is unimportant, only that individual
demographic traits may be poor correlates of r.
Safriel & Ritte (1983) found the gastropod Cerithium scabridum Phil. to be a
better colonizer than C. caeruleum Sow., which they attributed to the higher r of
the former species. Case (1975) used a reproduction parameter, composed of
annual egg production and age at sexual maturation, and adult survivorship in
his analysis of lizard distributions on islands, but could not find any correlation
between these two parameters and the number of islands occupied. However, if
these two parameters are combined into one, which resembles A/p, a general
concordance with the number of occupied islands emerges, albeit in a very small
sample (my analysis).
116
T. EBENHARD
In an analysis of bird invasions in Great Britain, O’Connor (1986) found
larger and more frequent clutches in species which have recently invaded the
British Isles, in comparison with sporadically occurring species which have not
done so. An increased egg-production probably increases A, and as O’Connor
argued that the number of clutches does not increase adult mortality, this would
suggest a higher r and Alp in species with large and more frequent clutches.
Lawton & Brown (1986) made a broad analysis of all animal taxa which have
recently invaded Great Britain. They assumed both r and the level of abundance
variation to be negatively correlated with body length, and then used body
length as a demographic parameter. The general pattern found was that large
animals were better colonizers than small ones, despite their lower r, because
of lower levels of fluctuations. Amongst the insects, however, they found the
opposite results. Both Lawton & Brown, as well as Williamson & Brown (1986),
doubted whether r in itself is a good determinant of colonization success, and
stressed the difficulties in finding common traits in good colonizers.
A different approach was taken by Lomolino (1984), who argued that
frequent colonization events in a metapopulation would give rise to selection for
traits that increase colonization success. He found a trend in body size of
meadow voles (Microtus pennsyluanicus), with heavier voles on more distant
islands. Lomolino (1 984) argued that this result was due to immigrant selection
during dispersal from the mainland to the islands, as large voles are better
swimmers than small ones.
Analogously, Ranta & As (1982) found a higher proportion of longwinged
carabid beetle species on Dutch polder islands than on the adjacent mainland,
implying dispersal capabilities to be of importance for colonization success.
Hanski, Peltonen & Kaski (unpublished) found longer hind legs in shrews (Sorex
araneus L.) dispersing to small islands in a Finnish lake. Such attributes that
increase the individual’s probability of successful dispersal, also increase the
immigration rate and hence the propagule size.
Ebenhard (1990) compared in a laboratory study the rate of reproduction of
field voles (Microtus agrestis) from the Stockholm archipelago in the Baltic Sea
and the mainland. The island voles were considerably heavier, grew faster, had
larger and heavier litters, and made a larger reproductive effort in relation to
their body size than the mainland voles. The duration of gravidity and the age of
sexual maturity were similar in the two laboratory colonies. This pattern of life
history traits found in the island population does not fit the description of an
r-selected species, but probably both r and Alp are larger in the island voles. The
large body size may additionally be an adaptation to swimming in cold water. In
neither this study nor in Lomolino’s study can adaptation to the island habitat
itself be ruled out as an alternative to colonization selection.
Despite the difficulties in distinguishing between different determinants of
colonization success in the analysis of distribution patterns, some conclusions
may be drawn. A good colonizer is often a generalist with good dispersal abilities
and a high reproductive rate (A).
As suggested by Hanski & Ranta (1983), there may be a trade-off between
being a good colonizer and being able to persist for a long time in a habitat
patch, e.g. due to good competitive ability. Hutchinson’s (1951) concept of
fugitive species, Diamond’s (1974) idea of supertramps, as well as the classical
r-K dichotomy (Pianka, 1970) rest on such notions. Peltonen & Hanski
COLONIZATION IN METAPOPULATIONS
117
(unpublished) found that the common shrew (Sorex uruneus) was a better
disperser than the smaller pygmy shrew (S. minulus L.), which, however, was
offset by the assumed lower mortality in the smaller species, due to its lower per
capita food requirements, resulting in similar colonizing abilities. O n the other
hand, Simberloff (1981) did not find any trade-off between colonization ability
and persistence time in his study of mangrove island insects, nor did Rydin &
BorgegHrd (unpublished) in their study of plants on small islands in Lake
Hjalmaren, Sweden.
DISCUSSION
Unless the regional persistence of a species is ensured by large, more or less
permanent source patches (Boorman & Levitt, 1973; Schoener & Spiller, 1987;
Harrison, Murphy & Ehrlich, 1988), the colonization ability of a species will be
crucial to its survival in a patchy habitat.
All four colonization models reviewed here predict demographic parameters
and propagule size to be important determinants of colonization success. This
prediction is supported by empirical data, especially by the results of
experimental colonizations. However, the field data are not detailed enough to
weigh the contributions of different demographic parameters, such as r and A/p,
nor can we say which theoretical model most closely predicts colonization
success. The models also suggest that a large propagule size, which is a function
of, for example, dispersal ability, is more crucial when the rate of population
increase ( d / p or r ) is low, and conversely that a high rate of increase is more
crucial when propagules are small. This implies that ecologically dissimilar
species may be equally successful survivors in a fragmented habitat, relying on
different strategies. Some generalizations about the attributes of good colonizers,
such as being a generalist and a selfer, are supported by data, but others are not,
e.g. being ‘r-selected’.
In three of the four colonization models, including the most commonly used
MacArthur/Wilson ( 1967) model, only demographic stochasticity is assumed.
When a population is small, as it almost always is in the beginning of a
colonization, demographic stochasticity is thought to be more important than
environmental stochasticity in causing fluctuations in population size. Early
models (e.g. Richter-Dyn & Goel, 1972) indicated that only populations smaller
than 20 would be affected by demographic stochasticity, but more recent
literature has increased that figure towards at least 100 (Shaffer, 1987; Lande,
1988; Forney & Gilpin, 1989), partly due to the variation in population size
induced by heterogeneous demography (Ebenhard, unpublished). Furthermore,
the colonization may be a fast process in relation to environmental fluctuations,
so that a colonization event takes place within a time period of relative
constancy, given values of d and p set by the environment and its variation. Each
colonization attempt would then take place under different conditions, but the
process would be adequately described by a model with only demographic
stochasticity. Environmental stochasticity may thus determine when colonization
success would be more probable, but during the colonization process itself,
especially initially when the population is small, demographic stochasticity
would be more critical.
T. EBENHARD
118
The conclusion to be drawn from this review, is that the extinction
probabilities may be considerably higher for a colonizing population than for an
established one, and may be determined by a different set of parameters (e.g.
Alp, instead of r ) . When designing metapopulation models and analysing real
metapopulations this fact should be considered. The exact way to introduce a
colonization probability in a metapopulation model depends on the basic
assumptions made, but in general within-patch dynamics must be recognized,
not just between-patch dynamics as in the original Levins model.
This review also has implications for the management of species living in a
patchy habitat. General attributes of a good colonizer have been recognized by
both theoretical and empirical studies, but actual values of demographic
parameters, as well as dispersal abilities, may be very different even between
closely related species. This means that the vulnerability of a threatened species
in fragmented areas cannot be assessed without careful autecological studies
(Gilpin & SoulC, 1986; Gilpin, 1987). In general, colonization models and
empirical results suggest that short distances between habitat patches, habitat
corridors (Noss, 1987; Simberloff & Cox, 1987), and a high quality matrix
increase colonization probabilities by increasing immigration of individuals.
ACKNOWLEDGEMENTS
I am indebted to Michael Gilpin and Ilkka Hanski, who invited me to the
Lammi symposium on metapopulations, and helped me organize my thoughts
into a paper. Jan Bengtsson, Lennart Hansson, Susan Harrison and Per Sjogren
all gave helpful comments on the original manuscript, and all the participants at
the meeting provided good discussions. Astrid Ulfstrand drew the figure. My
work is funded by the Swedish Environmental Protection Agency.
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