Metapopulations and Patch Dynamics:
Animal dispersal in heterogeneous landscapes
Tanya Rohrbach (rohrbach@rci.rutgers.edu)
Metapopulations in the Context of Patch Dynamics
A Closer Look at Metapopulations
Modeling a Determinant of Metapopulation Persistence: Animal Movement
Implication for Conservation of Animal Populations
Metapopulations in the Context of Patch Dynamics
A ‘metapopulation’ is a “population of populations” (Levins 1969,1970); in which
distinct subpopulations (local populations) occupy spatially separated patches of habitat.
The habitat patches exist within a matrix of unsuitable space, but organism movement
among patches does occur, and interaction among subpopulations maintains the
metapopulation. This view of a population structure emphasizes the position of
populations in space, and implies a concern for the interaction capability of spatially
discrete populations. Interaction between habitat patches occurs via dispersal as
individuals move among patches (Fahrig and Paloheimo 1988, Kareiva 1990, Wu 1993).
A Levins-type metapopulation exists when dispersal rates are “low-moderate” (Cronin
2003), meaning that an individual will move from one patch to another at a rate high
enough to maintain some interaction among subpopulations but low enough that those
subpopulations remain distinct. In cases where dispersal is rare, population dynamics are
directed by within-patch processes. High rates of dispersal lead to the unification of
patches into a single large, patchy population (Cronin 2003). All “patchy” populations
are not necessarily metapopulations (Hanski and Simberloff 1997), and there are different
types of metapopulations that deviate from one or more of the Levins-model assumptions
(Harrison and Taylor 1997) (Figure 1).
Figure 1. Types of spatially structured
populations. Shaded patches are occupied;
white patches are vacant.
(figure adapted from
Harrison and Taylor 1997)
Metapopulation theory is particularly useful to
wildlife biologists because most wildlife habitats
are fragmented or maintain some degree of
patchiness, and the idea of population persistence
being achieved even as local populations
Classic (Levins)
metapopulation
Mainland-island
metapopulation
Nonequilibrium
metapopulation
Patchy population
undergo extinction is appealing under such
circumstances (Wiens 1996). Animal dispersal among patches is an obvious concern for
populations existing in heterogeneous landscapes. Rate of animal dispersal is affected by
aspects of life history traits and population dynamics, but animal movement is also
affected by aspects of landscape heterogeneity, including patch size, patch isolation, edge
characteristics, and matrix characteristics (Fahrig and Merriam 1985, Gustafson and
Gardner 1996, Wiens 1997, Fahrig and Paloheimo 1988, Turner et al. 2001, Cronin
2003). Changes in patch characteristics, or “patch dynamics”, can have an effect on
processes of animal movement between habitat patches in a metapopulation, and
consequently could affect local population dynamics, including effects on the turnover of
local populations.
The relative probability of extinction and recolonization is a central tenet of
metapopulation theory (Hanski and Simberloff 1997), and dictates the viability of the
metapopulation. A metapopulation model suggests that regional population stability
(persistence from extinction) could be strengthened when the population is divided into
distinct subpopulations because unstable dynamics at the local subpopulation level could
be stable at the regional metapopulation level (Weins 1996). Regional stability is
strengthened as individuals disperse from habitat patches that have not suffered
extinction to recolonize empty habitat patches (Hanski 1985, Fahrig and Paloheimo 1988,
Adler and Nuernberger1994). Consequently, subpopulations may experience extinction
and recolonization, while the regional population (metapopulation) remains relatively
stable.
In proceeding from this discussion of the nature of metapopulations in the context of
patch dynamics, it is necessary to first gain a better understanding of metapopulation
theory before moving on to the importance of and methods of understanding animal
dispersal in this framework, and finally the implications for conservation of animal
metapopulations.
A Closer Look at Metapopulations
The adoption of the metapopulation model has been viewed as a paradigm shift from the
previously prevailing theory of island biogeography (Hanski 1989, Turner et al. 2001).
The theory of island biogeography (MacArthur and Wilson 1967) was developed to
predict the number of species that would exist on ocean islands and assumes a state of
equilibrium that is a function of island size and distance from the mainland source of
colonists. Metapopulation models generally embrace a more dynamic view of ecological
processes and can incorporate local mechanisms of population dynamics (Hanski 1998).
Both Levins’ and MacArthur and Wilson’s models have provided the context in which to
characterize the persistence of a population in terms of colonization and extinction rates
(Gustafson and Gardner 1996).
In metapopulations, extinction
Box 1. Conditions of a Levin-type metapopulation.
and recolonization are
1.
Suitable habitat occurs in discrete patches where local
breeding populations may exist.
2.
All local populations have a substantial risk of extinction.
If this were not true, a mainland-island metapopulation
would be evident because the persistence of the
metapopulation would depend simply on the persistence of
the largest population.
3.
The isolation of patches does not prevent recolonization. If
recolonization could not occur, the metapopulation would
be in a state of nonequilibrium and in danger of extinction.
4.
The dynamics among local populations are not completely
synchronous. If local populations experienced processes
simultaneously, the persistence of the metapopulation
would depend only on the persistence of the local
population with the smallest risk of extinction.
dynamically recurring in
subpopulations. An important
factor affecting the viability of a
Levins-type metapopulation is
whether the replacement
condition of subpopulations is
met (Hanski 1998). The
replacement condition
necessitates that, in the course of
its duration, a subpopulation generate at least one new subpopulation. This can be
expressed as a colonization-extinction dynamic, in which recolonization must be
sufficient to compensate for extinctions (Hanski 1997, 1998). Because it is this
dynamically maintained balance that leads to metapopulation persistence, it is possible
for a metapopulation to experience extinction even if all subpopulations are not
eliminated (Nee and May 1992). Hanski (1997) suggests that in a population where four
specified conditions are met, a Levins-based metapopulation model is applicable (See
Box 1).
In addition to the criteria outlined by Hanski, the classic Levins model holds simplifying
assumptions regarding spatial context. Firstly, habitat patches are seen to exist in a
binary relationship with the surrounding matrix and are relatively small, being only large
enough to maintain a viable local population. Additionally, habitat patches are assumed
to have equal areas and isolation.
The application of Levins’ metapopulation model is becoming widely recognized, but the
understanding that real populations do not adhere to all the assumptions of the classic
metapopulation model has been noted (Hanski and Simberloff 1997, Hanski 1997,
Harrison and Taylor 1997, Cronin 2003). Consequently, a number of variations on
Levins’ classic model have been developed to better incorporate aspects of landscape
heterogeneity, such as details of patch sizes, patch clumping, individual movement
capacities, local patch dynamics, and explicit patch locations (Johnson et al. 1992, Wiens
1997). For example, Adler and Nuernberger (1994) challenged the two assumptions of
equal connectivity among all patches and simplified within-patch population dynamics.
They applied a simulation model to demonstrate the effect of habitat arrangement on
dispersers and to evaluate the distribution of individuals across the landscape. This type
of metapopulation study has led to alternative versions of Levins’ model that incorporate
greater complexity, allowing for the study of real populations existing in heterogeneous
landscapes.
Modeling a Determinant of Metapopulation Persistence: Animal Movement
Local population turnover and inter-patch colonization are two dominant forces
influencing metapopulation dynamics (Wu 1994), indicating that the movement of
organisms between patches is a key aspect of metapopulation dynamics and persistence
(Hanski 1985, Gustafson and Gardner 1996, Weins 1996, Cronin 2003). If dispersal
between patches cannot occur, then recolonization conditions will not be satisfied.
However, despite the recognized importance of attaining knowledge of animal
movement, very little is known about animal dispersal patterns and dynamics for most
species (Wiens 1996). Collecting data for between-patch dispersal rates is difficult, and
studies of dispersal processes are generally not attempted (Kareiva 1990, Gustafson and
Gardner 1996, Cronin 2003). Given these circumstances, mathematical models
addressing dispersal have become particularly important in theoretical and empirical
studies concerning the relationship among population dynamics, animal movement, and
landscape structure.
Mathematical models that attempt to describe ecological processes in patchy landscapes
vary in representation of spatial heterogeneity (Kareiva 1990). Island models are
spatially implicit, meaning that they have no spatial dimension and portray patches to be
equally accessible to one another. Levins’ classic metapopulation model is of this type.
Spatially explicit models describe patches as having fixed spatial coordinates, which
allows for variation of dispersal distances. Spatially explicit population models (SEPMs)
allow the user to specify the location of each object of interest within a heterogeneous
landscape, enabling the relationship between habitat patches of a population and other
landscape features to be defined (Dunning et al. 1995).
SEPMs, in particular, are becoming important tools in evaluating population dynamics in
heterogeneous landscapes (Dunning et al. 1995). They allow investigation and prediction
of organism response to landscape changes that are difficult to study empirically due to
broad scales and ecological complexity (Turner et al. 1995). Furthermore, analytical
models are not sufficient to address the effect of patch dynamics relating to patch
composition and configuration because they do not include information on patch
characteristics or location (Pulliam et al. 1992, Dunning et al. 1995, Hanski 1997).
SEPMs, however, are spatially realistic and can represent a specific population operating
in a specific landscape. An important distinction between SEPMs and other landscape
models is that SEPMs can represent animal movement at the organism level to show
individuals moving between patches, and quantify the effect of this movement on
population dynamics (Dunning et al. 1995).
Individual-based models are SEPMs that monitor the location of individual animals as
they move across a landscape and can present a useful tool for evaluating relationships
between animal movement and patch dynamics in the context of metapopulations.
Gustafson and Gardner (1996) developed an individual-based dispersal model to measure
immigration and emigration rates between habitat patches in a spatially explicit
landscape. The model was intended to estimate the effect of varying landscape
heterogeneity on the transfer probability of dispersers between habitat patches and to
visualize movement corridors and barriers as perceived by animals operating according to
specified movement rules at specified scales. The results showed that differences in the
size and distance of habitat patches accounted for 89% of the variability in dispersal
success (i.e. movement from one patch to another within a specified number of steps).
Individuals were also shown to move through preferred ‘corridors’ of dispersal, although
these movement pathways did not enhance overall dispersal success because they were
randomly arranged. An asymmetrical relationship between immigration and emigration
rates within actual landscapes was also shown to frequently exist, and a change in matrix
heterogeneity made at least a two-fold difference in dispersal success for some patches.
This finding suggests that the deviations in size, shape, and arrangement of patches
within a heterogeneous landscape matrix will affect in which direction movement is more
favorable (Gustafson and Gardner 1996). This type of application of an individual-based
model can improve estimates of animal dispersal in metapopulation models, and the
results show the importance of landscape context on studying metapopulations.
SEPMs can also have application to real world problems. Because SEPMs can be used to
examine or predict possible population responses to changes in actual landscapes, they
can provide promising tools to conservation and management of animal populations
within heterogeneous landscapes (Pulliam et al. 1992, Dunning et al. 1995, Cramer and
Portier 2001). Pulliam et al. (1992) developed a class of SEPMs called MAP (Mobile
Animal Population) in order to evaluate how the demographic and dispersal
characteristics of populations, combined with the changes in the availability of suitable
habitat, affect population size. They applied three categories of variables that they claim
should be incorporated into any model of the population dynamics of a mobile species
inhabiting a complex landscape: 1) landscape variables describing habitat abundance and
the spatial arrangement of habitats, 2) habitat-specific demographic variables, and 3)
behavioral variables describing the dispersal characteristics of the species. Because
metapopulation theory is based on the ability of dispersers (i.e. mobile species) to
recolonize habitat patches, these three categories of variables are applicable to the study
of metapopulation dynamics. Simulations of the model evaluated how the population
size and extinction probability differed when variables within each of the three categories
were altered. The findings showed that the increase in population size resulting from the
presence of habitat patches as sources of dispersers decreases probability of extinction.
The results of this and comparable models can direct current management plans in their
attempt to increase the probability of metapopulation persistence. SEPMs are valued
models for making real world predictions concerning conservation (Hanski 1997, Pulliam
1992), and spatially explicit formulations can greatly enhance the capability of
metapopulation theory to address conservation (Weins 1996).
Implication For Conservation of Animal Populations
Metapopulation theory, with its focus on landscape characteristics and population
persistence, is directly applicable to the conservation of populations existing in patchy
distributions. The relevance of metapopulation theory to wildlife conservation and
management has been recently recognized in the face of increasingly rapid habitat
fragmentation (McCullough 1996, Hanski 1998). The resurgence of metapopulation
thinking occurred when it was noticed that remnant patches too small to support
populations still persisted after habitat had been fragmented. This led to the recognition
that populations occupying small patches may be able to avoid extinction by dispersing
among many habitat patches (McCullough 1996). While management in largely
contiguous habitats emphasizes habitat quality within patches, fragmented landscapes
demand a focus on maintaining connectivity among local populations (Noon and
McKelvey 1996).
The metapopulation approach to wildlife management has been most developed for
management of the spotted owl (Strix occidentalis), a species which demonstrates the
variation and complexity encompassed by metapopulation dynamics (Gutiérrez and
Harrison 1996). Spatially explicit simulation models were developed for owl
populations, and results suggested that a viable metapopulation could persist over a
network of habitat patches of specified sizes and distances (Gutiérrez and Harrison 1996).
Application of metapopulation theory to the spotted owl case represented a shift in
management thinking from a focus on effective population size toward an emphasis on
the spatial arrangement of habitat (Gutiérrez and Harrison 1996), and incorporated
concepts of landscape ecology into conservation biology, with an emphasis on population
ecology.
The need to understand population dynamics in heterogeneous landscapes, especially in
the case of habitat fragmentation, has made it essential to integrate ideas from
metapopulation theory and landscape ecology (Wiens 1997). Conservation biology is
often concerned with the persistence of wildlife populations under different landscape
scenarios, and the effects of patch dynamics on wildlife populations are of major concern
in this regard. An important determinant of population persistence of animal species in
heterogeneous landscapes is dispersal ability, and Wiens (1997) contends that the key to
management of populations existing in a heterogeneous landscape lies in understanding
the effect of landscape structure on movement patterns within and among habitat patches.
A number of mathematical models are currently being developed and applied to evaluate
relationships among population dynamics, animal movement, and landscape
characteristics, most notably in regard to the conservation of fragmented animal
populations. Concepts from landscape ecology, population ecology, and conservation
biology are all essential to this understanding.
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